Rapid Platform – Abylon

Five Biggest Challenges in Financial Planning

Zoltán Zicherman — Wed, 07 Feb 2024 09:29:14 +0000

Intro

In our latest blog post, we delve into the five most significant hurdles faced in the realm of financial planning, ranging from the tedious manual consolidation of Excel files to the daunting task of ensuring data quality. We’ll explore how these issues not only consume valuable time but also detract from the core activities that truly add value to your organization.

1 - Manual consolidation of Excel files

When your operation expands beyond a solo venture, financial planning becomes a collaborative effort. Initially, companies tend to plan using individual Excel files, which are later merged by controllers and FP&A (Financial Planning & Analysis) colleagues to create a comprehensive overview.

This is what I mean by “manual consolidation of Excel files”

While this is a standard process for startups and small companies (actually, below a given size it’s overkill to do it otherwise), it becomes inefficient under tight deadlines or when it proves too costly or labor-intensive.

2 - Resistance to New Planning Tools

This leads us to our next big problem. Once you decide to go further and change to a more sophisticated planning tool UI/UX problems arise. Let’s be honest: users who typically provide the initial data during the planning phase, have a day-time job and might be more familiar with Excel than a new, possibly web-based, tool designed for planning (the one you plan to replace Excel).

Learning a new tool just to input new data… That’s too inconvenient. Forcing this will potentially lead to conflicts, at least. (Not to speak of the costs of a web-based UI, and the development, and testing during the implementation phase of such a system)

3 - Challenges in Tracking Progress

Let’s say that you tackled the above. You created a data pipeline which can read from multiple files. You may be able to track, which file arrived when, and which has been consumed when. But, do you have a method, to keep track of which numbers have been approved?

Oh, you mean… This is part of the job who provides the files?

This means, you are not tracking the entire process, and you have no proof, if something has been approved, or not… Without a clear method to track approvals and updates, you lack visibility into the process.

Progression tracking in advanced tools facilitate better tracking of each data point’s status, ensuring a transparent and verifiable planning process.

4 - Your experts doing avoidable tasks

A well-designed system can help avoid tasks that detract from efficiency, such as:

Preparing the Excel files for the planners. Pulling the reports only relevant to them, and what they can see. This is what we call: Row Level Security
Validating forecasted data on the granular level.
Updating reports for planners after changes.
Manually monitoring planning progress within the organization.
Managing the planning process through continuous requests for files, corrections, and updates.

5 - Data Quality issues

Everybody makes mistakes. Manual processes are error-prone, and while manual error-checking can reduce mistakes, but since it is also carried out by humans means errors can still occur.

An effective system prevents flawed data being saved into the database, enhancing overall data integrity.

The Paramount Issue: Time

Ultimately, all of the above add up to one huge issue -> taking precious time away from you and your team. Time which could be a better spent on activities that add value to your organization, such as analyzing what happened, communicating the numbers, building narratives with the stakeholders, predicting the future.

We believe that being a true business partner like a CFO or a FP&A leader means focusing on these activities. Therefor it is a logical step to invest into a tool that solves all of the above problems, and maybe provides industry-specific solutions for you as well. Like a template and configuration possibilities to easily plan software licence sales.

Why Our FP&A Solution Stands Out?

Our Financial Planning Solution

is Excel-based,
has a mature core technology background,
has a rich feature set, like:
– Master Data handling
– ETL processing,
– DataWarehouse building capabilities,
– Custom and Predefined Excel-templates,
– Common business logic taking care of the heavy lifting, and
– Software license sales – specific templates

Our Philosophy

We don’t believe that “one-size-fits-all”.
We believe that tech-people should do their part, and finance people should do theirs
We believe in customizable, industry-specific templates

The Ultimate Value of Financial Planning

The greatest value is that planning and finance creates a common ground for communication within an organization. Money is the language, every action in a business can be transformed, and communicated.

An FP&A/Controlling leader’s greatest value is supporting stakeholders within in an organization to be able to communicate based on a trusted, single source of truth that is accepted among the participants.

Everything else supports the above. What is everything else?

Analytics, Reporting, Month-end and Year-end closings, Planning and Forecasting.

More on Financial Planning and Analysis

For more information check out some of our other blogposts about the Rapid Platform and our FP&A solution Abylon Rapid Planner:

The post Five Biggest Challenges in Financial Planning appeared first on Abylon.

Data warehouse project using the Abylon Rapid Platform

Zoltán Zicherman — Wed, 04 Oct 2023 10:32:50 +0000

Automated SQL Data Warehouse project done in 3 weeks with minimal prior experience

Data warehouse implementation - easier than expected

As a junior BI consultant with 10 months of work experience, I was given the task to build a complete data warehouse, data marketplace and populate it with data.

Considering that I had little experience in the field, this task promised to be a time and energy consuming challenge. I did have some help from a senior colleague who monitored and supported me during the process, but this did not change the fact that I had to understand and complete a complex process without any prior experience.

All I had to do was:

understand the steps of the process,
define the structure of the data warehouse, the objects to be fetched from the source system,
and put them into a simple Excel-based configuration file.

By setting up the configuration file properly, the creation of the new data warehouse could be almost completely automated.

The parameters I needed to set up the configuration were the availability of the different source systems, the objects to be fetched from them, any changes to the objects (e.g. columns of a table, data type of a field, name), how they are loaded, how they are historized and other optional parameters, the steps of the ETL processes that load the data, and the availability of the target system. Having all this in one place allowed me to quickly check and modify the structure if changes were needed.

After definig the metadata, the Rapid Platform was able to automatically create the different database layers (stage, data warehouse, data marketplace), by running a PowerShell command, on the specified target server, which in my case was an MS SQL database server.

The benefit of the solution lies not only in the ease of use for Business Intelligence developers, but also in the significant time saving (and therefore cost reduction) that it brings. The time and energy freed up through the automations could be spent on deeper analysis of the task and the data, and through that on tasks that actually create business value, such as designing and refining the right data model and subsequently producing analytical reports on those models.

A few words about the environment

In a Microsoft stack-based development environment, a data warehouse automation solution can be easily implemented with the Abylon Rapid Platform.

Quick overview of process of generating a data warehouse and the software used during the project:

Using MS Visual Studio, the configuration files for the data structure, the server connections and the project environments, can be easily accessed and modified. There is also a configuration file that stores the connections and environments.

After loading a specific tool from the Rapid platform, I used a simple PowerShell command to generate the files defining the STAGE, DWH layers as part of the solution.

After creating the build in Visual Studio, running another Rapid Platform command, the given data model structure is deployed to the given SQL server (if the connections are defined correctly). I then created the different OLAP models, which I could build in Visual Studio as well as in Tabular editor. I could then deploy this to an Analysis Services server using an separate command.

After that, I only needed to transfer the data. The “how” I already defined in the configuration file. The stored procedures for transferring data from the STAGE layer to the DWH layer were automatically generated. The invocation of these stored procedures can be simply added as “execution plan items” to the configuration file as part of various “Execution Plans” that can be easily invoked and scheduled by a SQL job. The manually created stored procedures that fill the DM layer can also be added to the part defining the ETL process inside the configuration file and then can be run as part of the “Execution Plan” when runing the SQL job. This allows the loading of the entire data warehouse with a single job execution.

This created an automatically updating data warehouse with the necessary data historization available, as well as the OLAP cubes. After connecting to the latter I could starts generating the various analytical reports.

Despite the fact that this was the first time I was using the Rapid Platform, and generally speaking I did not have much DWH experience, thanks to the flexibility and simplicity of the platform, the whole process, including the subsequent improvements required by the client, did not take more than 2-3 weeks.

The main benefits I have experienced

In addition to taking a huge burden off the shoulders of the developers, data warehouse automation is also a significant benefit for the customer, as it can greatly reduce the time and effort spent on an DWH implementation.

The benefits of automatisations

Ease of use

Flexibility

Case Study: Sales planning automation

Zoltán Zicherman — Mon, 18 Sep 2023 13:15:49 +0000

Below, you’ll find a detailed case study that offers an inside look into a planning automation project we recently executed for a major software company. For this edition, we’ve opted for a more narrative approach to provide a personal and insightful perspective. We hope you find this storytelling format both enjoyable and informative.

Project Background

Sales planning can be a daunting task, one that Julie knew all too well as she stared at the 22nd Excel file that had landed in her inbox that day. The seemingly never-ending process required intricate calculations involving #deferrals, #sales, and #revenues, all of which were pivotal to the sales team, and therefore the whole company’s success.

In a software company where sales were tied to various software licenses, the complexity of sales planning was undeniable. For Julie and the rest of the colleagues involved in planning, this process was slow, ineffective, involved a lot of manual work and to put it nicely, it was far from enjoyable.

Business Challenge: Data Preparation and Calculation Complexity

The first challenge lay in the preparation of historical data for each customer group. It was no simple task. Sales representatives had to input the number of units to be sold, but Excel couldn’t instantly recalculate what this meant for Sales Amount and Revenue Amount. This meant that both Sales Amount (Quantity * Price) and Revenue (Sales Amount +/- Deferrals) had to be calculated for every planning period. Furthermore, sales teams had to predict Renewal rates and Price increases for each product in their region, which directly impacted historical data.

The enormity of this task became apparent, especially for customer groups with hundreds of thousands of records requiring calculations. Excel, on its own, couldn’t handle the complexity.

Exploring Solutions

Two major directions were considered to tackle this challenge: bringing the planner closer to the “tech” or bringing the “tech” closer to the planner.

Bringing the planner closer to the “tech”:

This approach involved having planners embrace new technologies. However, it was evident that not everyone was tech-savvy, and expecting them to learn new technologies for a process that wasn’t their primary focus seemed impractical.

Bringing the “tech” closer to the planner:

This approach aimed to provide a user-friendly interface for planners. While promising, it raised questions about design, tabular data handling, frontend development resources, and the learning curve for planners. Questions like:

what kind of design should we use?
how should one address the tabular data? Save each line? Recalculate on every mouse-move?
how can we display effectively more than one kind of tables which are related to each other?
how many hours of a Front-End development is needed, when will they be available?
who will create the design?
how will the planners learn the logic of the new design, and the new frontend, if it’s not intuitive enough?

By choosing Excel as the frontend, we addressed many of these concerns.

Our Solution

Given the complexity of the project it seemed a perfect case for Abylon Rapid Planner – the planning module of the Abylon Rapid Platform.

The Rapid Platform itself is a flexible, enterprise grade productivity platform for building Microsoft Data Warehouse or Data Lake based analytical solutions. On top of the platform, we created easy-to-deploy business solutions for the most common BI and data analytics scenarios.

The planning module we used in this case includes enterprise-grade financial and analytical planning, master data management, querying and scenario-analysis.

Abylon Rapid Planner offers Excel’s functionality scaled to the enterprise level. Database connections, automated data validation and easy business template creation – all to minimize manual work.

Implementing Abylon Rapid Planner effectively resolved all the key issues, with the exception of incoming data cleaning, as per the client’s decision due to ongoing source system discussions.

Results

With the Abylon Rapid Platform, everyone can access their relevant data from within Excel securely. Unauthorized access is prevented, ensuring data integrity.

Once data is provided, recalculation happens instantly, eliminating manual work. This has a profound impact on reducing manual tasks during planning and forecasting periods, as well as significantly reducing waiting times for Sales Planners.

The platform simplifies the entire planning process. It eliminates manual data sending, consolidation, and recalculation. Custom data validations ensure data consistency, and plan versions can be easily tracked. The result is increased confidence in data accuracy and alignment with approved plans.

No additional automatization process or consolidation is needed in order to provide data to a Business Intelligence system, since the data is already organized and stored in a database, and is ready to be ingested.

The Abylon Rapid Platform offers a central master data management solution. It removes the need for manual updates, ensuring data consistency across the board.

Our platform provides ETL functionality (like mass upload) within Excel and beyond. It streamlines data upload and integration, eliminating the need for external ETL services.

Conclusion

In conclusion, the Abylon Rapid Platform revolutionizes sales planning by addressing the challenges faced head-on. It ensures data accuracy, reduces manual work, and streamlines the planning workflow. Say goodbye to complex Excel files and embrace a more efficient, user-friendly approach to sales planning!

If you’re ready to transform your sales planning process, contact us today to learn more about how Abylon Rapid Platform can benefit your organization.

For more information check out some of our other blogposts about the Rapid Platform and our FP&A solution Abylon Rapid Planner:

The post Case Study: Sales planning automation appeared first on Abylon.

Effective Master Data Management with the Abylon Rapid Platform

Zoltán Zicherman — Mon, 16 Jan 2023 14:51:27 +0000

Effective Master Data Management with the Abylon Rapid Platform

Who needs Master Data Management?

If You already know, that you need Master Data management, feel free to skip this part and jump right here! This quick overview helps you to understand the business needs why a company might need a master data management tool and to provide some real-life business use-cases.

Imagine a Business Intelligence (BI)-system! – Ok, but how? – You might ask, and really, what is the substance in business terms of a BI-system (BI as Business Intelligence). I won’t be going into that in academic terms, but one way to look at BI-systems is that:

„A Business Intelligence system is a solution package, which gathers data from one or several source systems in order to create reports from it.”

Please also let me hereby express my apologies to true BI-developers. They probably have a much better definition, but for now, and for the sake of simplicity, let’s stick with this definition.

Imagine, that you have a BI-system. It works with data coming from various source systems, data like: users, customers, vendors, and so on.

Use case I. - Basic categorization

You want to categorize your vendors in a new way, to make a new report but in your ERP system (a source system for the BI in this case) there is no field or option currently for that kind of categorization, and it would take a lot of resources to add that field. This custom development is not on the development road map, but you still have to create a report using this categorization. Maybe you have to build reports on this ground, maybe you have to build/develop even more operational stuff.

Use case II. - Tax report change

Imagine that for some reason the international tax-environment changes (or will likely to change very soon), and the reports you’re taking care of need a rapid readjustment for planning, but operationally you are not able to change the source-system’s tax-categorization data.

Use case III. - Integration of new ERP system

Your company is implementing a new ERP-system, but you have one or multiple legacy systems, which have dimension attributes (for example: categorizations of vendors) in the legacy system(s) and in the current bi-system, which are already in place, but the new system is based on a different logic, thus this kind of categorization will be replaced, but you don’t want to change all your reporting structures straight up since the new system will be implemented in the long-run, country-by-country.

Use case IV. - Affiliates with different accounting systems

You are working with several affiliates who use various, custom accounting source systems and different book of accounts structures. However, you still need to create reports using their data. This means you need to manually consolidate all of this data and arrange it into your own data categories, dimensions and reporting structure.

Downsides of the "old-school" approach to Master Data Management

If you’re coming from business (as I do) your first idea to solve any of the above use cases is to gather all the data in Excel-files. Then, eventually put them in a some SharePoint folder and then share the Excel files across multiple users throughout the globe. Right? This is a legit approach right?

Yes it is, if you’re absolutely comfortable with the „Demons of the Shadow IT” haunting you utill the end of your practice at that company… I know what I’m talking about. I’ve built the shadow IT for years… Here are dome of the problems with this approach:

To put it simply, who should be able to access the data, and who should be able to adjust it?

How to manage if more than one user wants to work in it simultaneously? I know-I know: Excel is supposed to handle this. However we know there are issues there, like not saving something, if two or more persons are working on the same file at the same time.

How to know, what has been adjusted, who made the adjustments or edited the data (God-forgive deleted or added data), and what was the value before those actions took place? Actually this is a very common issue, when more than one person works with data. How can one be sure, that nobody touches their data, or if someone touches it can be traced back, so maybe there will be a discussion about the causes of the matter.

How to validate the values? Okay, Excel’s data validation is a viable an option here. We use it too. The problem is, that it can be easily overwritten, so it’s not a bullet-proof solution.

What if there are more complex validation rules that have to be applied? Validation based on some sort of business logic.

Imagine that you can only add data in a column which is between the min and max values of another table’s column’s data. Like you have to set monitor sizes, and there is a possible minimum and maximum value stored somewhere based on the available stock. How do you handle this?

Business Intelligence with adequate Master Data Management

Let’s start with usability! Just like with any other IT solution, usability, and therefore the User Interface is a key factor. What’s the best UI in this case? If you are guessing I hope you got it right! It’s the one and only MS Excel. I’m not joking. Excel is still the most universal (and most popular) tool for every controller or even office worker dealing with data.

Of course it has it weaknesses, so we gave our usual Excel UI some superpowers! We connected it to a database through our Excel add-in available directly in Excel itself. So what are the benefits of that? Let’s see a few:

Since we are connected to a standard SQL database, this connection can be used for any other standard purpose like being a data source for your queries, reports, or BI-system built somewhere else.

The back-end of the solution is a standard SQL database so most changes or developments to the solution only require SQL knowledge. Considering most modern enterprises usually have their own architecture and database-administrator team and often a few BI professionals as well, it means that the customer itself can participate in the development or customization of their own solution.

Once we are familiar with the solution, it is an easy task to configure and create new tables, or adjust existing ones.

Since the user interface is Excel itself, there is no need for business users to do any type of programming, they can simply take care of the data in Excel.

The solution has a standard way of keeping track of history data, and logging events, including information on who viewed the data and when.

You need to validate data based on columns in other data tables? No problem! All you need is a simple configuration setting to reference that column. Once configured, data will be validated inside Excel using its own validations, plus it will also be validated in the background. Additionally – and more importantly – the data will also be validated in the “background” (on the back-end, database level)

Simple validation rules are not enough and you need to have custom validations based on business rules? Again, no problem! Any rule that can be described logically (and is a straightforward logic), can be developed in SQL and placed in a custom validation script, so that your data can only have values which are allowed!

Modern enterprise-grade MDM in just a couple of weeks

I’m not a marketing person. I don’t like big words. I used to be one of those people who are ultimately the end-users of these solutions. Based on that experience I can say that once your company starts doing Master Data Management with the Abylon Rapid Platform is won’t just be a small step, but a huge jump toward efficiency. You will have a automated, flexible, easily customizable solution that radically reduces all the manual work related to any MDM-related task.

Moreover, because our solution is built on top of Excel – a familiar and widely used tool for users involved in these tasks – the implementation won’t take more that a couple of weeks!

If you want to improve your Master Data Management and what you just read sounds interesting give us 30 minutes of your time to present you our solution and show you that all the above is not just talk!

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The post Effective Master Data Management with the Abylon Rapid Platform appeared first on Abylon.

3+1 reasons why you need an Advanced Analytics Platform

Zoltán Zicherman — Fri, 09 Sep 2022 16:26:23 +0000

What is Advanced Business Intelligence or Advanced Analytics?

By Gartner’s definition: “Advanced Analytics is the autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations. Advanced analytic techniques include those such as data/text mining, machine learning, pattern matching, forecasting, visualization, semantic analysis, sentiment analysis, network and cluster analysis, multivariate statistics, graph analysis, simulation, complex event processing, neural networks.” (Source: Gartner Glossary)

In practice Python coding combined with some sort of Machine Learning development is usually called Advanced Analytics. You can realize business value from its output, but this output should be stored somewhere, as well as its input. To get the most out of Advanced Analytics, everything should be designed, planned and connected, which is usually much easier to do within a Platform.

Why would anyone need an Advanced Analytics platform?

1. Business benefits

All companies handle data. More and more every day. The magnitude only depends on the size of the company. Data from sales transactions, internal master data, product categories, etc.

This data has huge business value. The proper value can be discovered by data professionals, who can tell the current figures from past/present sales data, and can also predict the future, count efficiency rates, net margin, and many aspects you are curious about. But we can agree that without a clear understanding of this data a company can’t be successful in 2022.

According to Forbes, 95% of businesses cite the need to manage unstructured data as a problem for their business.

2. Technological modernization

Data professionals agree that data is still best stored in a database. Data professionals also agree that there might be more opportunities in raw data stored in databases, but it is usually two different worlds, relational databases and machine learning are not really close to each other.

The bridge between them is an advanced analytics platform, that can understand and serve both worlds very well, bringing out the best synergies from each.

3. Sustainability: lower and more dynamic costs

Locally: The platform’s costs are dynamic (use less, pay less), but also accurately predictable (hourly rates). Also, you don’t need to hassle with technical physical parts, and there is no need to keep a team of technician handymen standing by until they must urgently fix a serious outage. There is no such outage in Azure.

Globally: Way less energy consumption, and it is only consumed when it is really used. There are no idle blank spots (day vs night energy consumption) and the energy bill is paid by Microsoft, NOT you.

+1 The future of BI is in the cloud (or multi-cloud, or hybrid)

Not so long ago, all big companies stored their business data in their own, huge on-premise data centers. But maintaining and operating this type of infrastructure costs a lot of money and with the size of data growing exponentially this concept seems like a dead end. This led to the birth of the concept of cloud computing, offering a new era for data-oriented systems. Cloud computing is a lot more than a catchy buzzword; it is the next generation infrastructure that modern companies already use.

If your company is not on board yet, you’re already losing out to your competition. In a 2021 O’Reilly survey, 48% of participants said they plan to move most of their apps to a cloud during the next year.

While according to Gartner, companies will deploy 95% of new digital workloads on cloud-native platforms by 2025.

There are options even for those companies who have their security and data confidentiality concerns with the cloud. Services like Microsoft Azure allow you to keep some data on public servers while giving you the option to keep sensitive data on private servers so that you can actively control and monitor it.

An Advanced Analytics Platform is naturally built using cloud technology, and as cloud computing is the future of data systems, an advanced analytics platform is the future of analytics, reporting, and self-service BI.

How to get started?

Well it always depends on the type and size of your company, on the industry operate in, on your business case and your cloud and business intelligence “maturity”.

Abylon Consulting has delivered more that 200 successful BI projects in the past few years including Advanced Analytics projects utilizing Microsoft Azure and Synapse technology, so if you’re looking for a someone to fast-forward your company to modern era of data analytics contact us and let’s have a quick talk to see how we can help you!

If you are interested in the technical side of an Advanced Analytics Platform and you would like to give it a try check out this post that describes how to create a complete framework around cool buzzwords like “Python, ML and AI” working with industry-leading Microsoft products.

The post 3+1 reasons why you need an Advanced Analytics Platform appeared first on Abylon.

SSAS Tabular model management with the Abylon Rapid Platform

Zoltán Zicherman — Mon, 23 May 2022 15:25:22 +0000

Intro

In the context of a number of recent enhancements, we thought it is worthwhile to write up a brief summary of the Tabular model services available within the Abylon Rapid Platform and highlight how they support development, processing and logging.

Development

First of all, during development, tabular models can be deployed to any number of environments just like ETL processes, databases, reports (etc.). There is no need to rewrite the connections every time you move to a live environment, the platforms will do it for you after setting up the appropriate parameters. It also provides the possibility to publish user-level self-service models to a productive environment.

The developer’s life is made much easier by automating the creation of dynamic measure tables. Dynamic measure is useful for any business, but the creation and maintenance of the necessary tables and measures is time-consuming and sensitive to changes. Abylon Rapid Analytics takes this burden off the developer’s shoulders. It also makes it easy to produce measures based on selected measures such as LY, MTD, ALL, etc. based on calculation groups.

Processing

Our execution plan manager allows the usage of several OLAP processing steps in each execution plan item. Such as:

Full process, this is obvious
Dynamic partitioning, code-driven version: dynamic partitioning creates the partitions according to the configuration and processes the appropriate number. Main features: rolling window, incremental partitioning, incremental processing, fix interval.
Dynamic partitioning, data mart-driven: the data market developer has the possibility to create his own stored procedure, which passes the processing and creation command to the framework.

Logging

Metadata backup: main data of SSAS tabular models installed on environments, up to the query level of partitions.

SSAS instance monitoring: load, queries monitoring with Platform Planning functionality.

This is just a short teaser because this list could go on and on. We believe that, as with the whole Rapid Platform, in this case our strengths lies in the convenience of the ready-made solution, the cost-effective customization and the fast, customer-oriented development.

The available features do not set a mandatory direction, but provide opportunities, and the developments made during implementation help to fully meet the needs of our customers and provide support and good foundation for further BI development projects.

The post SSAS Tabular model management with the Abylon Rapid Platform appeared first on Abylon.

Excel with data validation and database connection

Zoltán Zicherman — Mon, 25 Apr 2022 10:36:48 +0000

Custom UI vs. Excel with database connection

How many data related software development projects have you seen, where there was a User Interface that should have stayed in Excel, if it had the capability to connect files online? I not talking about the default online editing, I mean really connect.

How many User Interfaces have you seen, that would have been better (and a lot more efficient) in Excel, if it had a proper data validation feature?

Of course, some people hate Excel, some people love Excel, and a lot of people only use Excel as a default office tool, like Word. There’s a lot of debate going on on the internet regarding this. I see articles at least a few times a year going on about whether Excel is already dead, and that everyone should use SQL, DAX, Notepad, pen and paper or basically any other tool, but for God’s sake, don’t use Excel!

However, I think (and I’m not the only one) Excel is a very efficient tool and it is here to stay. It is a very powerful tool, with a smooth learning curve and it has capabilities that other tools just don’t have. If you know it’s benefits, you know what I’m talking about. If you don’t there are plenty of online courses to get familiar with them. Don’t be put of by the fact that Excel is around for more 35 years. If you’ve seen any big company from the inside, you know it is still widely used for wide variety of use cases, simply, because it works.

Upgraded Excel with database connection any type of data projects

Now imagine, if Excel had two key capabilities:

Communicate with databases (store data, create data, get data, update, and delete data)
Validate the stored input, and give immediate feedback to the user when sending the requests to the database

BOOM! You get an application. You won’t get a fancy, colorful, online user interface, with huge text boxes.

But, what you’ll get is a tool that is:

With these extras the possibilities with Excel are almost infinite:

You can always get the accurate data from a database. You don’t have to check, whether someone – even you – accidentally hit a key or a button, and therefore your whole calculation is now gone, and you have to debug it in a huge Excel-file.
You can store new data without the possibility of overwriting former data, but with the capability to provide massive amount of validated data in an instance – instead of putting the data in a database form-by-form.
You can instantly take a look at who modified the data, when, and what changed. Historization can be a key feature.
You can connect your Excel files with a Business Intelligence system (like Abylon Rapid Platform’s ETL solution), and when getting the fact data you can always get the newest, freshest data!
You can instantly see your colleague’s planning data. Every modification takes effect instantly. You don’t have to process e-mails, download attachments, open Excel files, and administrate, which ones have you already taken care of, and which ones you haven’t yet. You may even have some back-end features, like e-mail sending, approving/rejecting data, etc.

So when we talk about Abylon Rapid Platform, we really talk about a Neuralink for Excel: adding infinite new possibilities to Excel.

Example Solution - Abylon Rapid Planner

Does your company use Excel for financial planning and forecasting? How about Excel on steroids? Break through the limits of spreadsheets with Abylon Rapid Planner – a tool that takes the intuitive functionality and flexibility of spreadsheets but adopts and scales it to the enterprise level!

Rapid Planner is ideal for making spreadsheet-based financial planning, budgeting and forecasting, financial controlling and literally any spreadsheet-based analytical planning, for any company size ranging from mid-sized companies right up to the enterprise level.

The post Excel with data validation and database connection appeared first on Abylon.

What clients say about Rapid Analytics?

Zoltán Zicherman — Tue, 16 Nov 2021 17:29:58 +0000

Interview: What our clients say about our DWH Automation tool

A few weeks ago we successfully completed a data warehouse project for Dashboard Solutions using our Data Warehouse Automation Solution – Abylon Rapid Analytics. In relation to this, we had a quick interview about with senior BI Architect Zoltán Nyircsák to get a quick feedback from the clients’ side.

Abylon: Thank you for taking the time for this quick interview. First of all, for what tasks do you use Abylon Rapid Analytics?

Zoltán Nyircsák: It is important to mention that we basically did not buy a technology or a component, but a solution. We chose Abylon and their data warehousing solution because the technology they used promised a quick rollout (and they kept that promise). But nonetheless, it was paramount that the experts were truly experts from both business and technology perspective. In fact, on the customer side we don’t even really need to understand what ARA (editor’s note: ARA stands for Abylon Rapid Analytics) does, it’s enough to articulate the business problem and then enjoy the benefits.

Abylon: How and to what extent does Abylon Rapid Analytics simplify your work?

Zoltán Nyircsák: Since the technological solution and its maintenance and development are not on the customer’s side, so it’s not easy to answer this question. However, we do enjoy the benefits from the business side. Eg: rapid development of data markets.

Abylon: How responsive is the solution (or Abylon?) How fast can it track changes?

Zoltán Nyircsák: The responsiveness is good. There were several source system changes that were easily handled by the solution. For example, there have been several overnight transitions to develop a new source system. Because we work with source systems that are in use, they are constantly changing, evolving, getting new features. So it was important for us that the BI solution we were building could handle this (with the help of Abylon experts, of course.)

Abylon: How flexible is the system?

Zoltán Nyircsák: So far, we have found a solution for everything together. Here again, I would like to point out that the technology used is “hidden” from us. This division of responsibilities between us and your experts was agreed prior to the project. Our part is to formulate the request, whether it’s some specific data, analysis, or business problem, and you give us the solution.

Abylon: How complicated do you find managing such a system?

Zoltán Nyircsák: This is also part of the service, so we don’t have to deal with it. However, the data warehouse and data market based on the solution, and the Power BI service, was an excellent choice. We are able to respond quickly to new business needs, facilitating the accurate, timely and reliable delivery of not only data but also information.

Abylon: What do you think, how much time did the use of Rapid Analytics saved you during your data warehouse building project?

Zoltán Nyircsák: Without it, it would’ve been an order of magnitude (I really mean the 10 times multiplier) more time and money to develop such a solution and then to adopt and react to all the changes. The development time has been largely reallocated and instead of spending time on manually creating the obligatory things, we were able to spend more time on the essential things and put more energy into the construction of the data market.

Abylon: Finally, what would be the feature that would make Abylon Rapid Analytics even more valuable to you?

Zoltán Nyircsák: Right now, we don’t really need anything else, but if I think about the future, maybe a built-in report on the operation of Abylon Rapid Analytics, the data loads and performance would be good.

If you are interested in our DWH Automation solution, head to the dedicated product page or contact us and we’ll be happy to answer your questions or arrange an online presentation

The post What clients say about Rapid Analytics? appeared first on Abylon.

How to post G/L records with retroactive data with the help of BI and SCD?

Zoltán Zicherman — Wed, 10 Nov 2021 15:04:57 +0000

For whom this blogpost is meant for

IT professionals who work with data, optionally familiar with BI or Datawarehouse technologies, and may need to create a solution in which they need to create posting files or an interface for accounting /ERP systems from historical data. This article can help them to identify the required actions and things to consider.

On the other hand, it is also intended for financial professionals or Business Analysts who are involved in a project or projects where the goal is to develop an interface between normal transaction systems and accounting/ERP systems.

Intro

What is posting in accounting?

If you know what an SCD, or even a SCD2 is, feel free to jump on to the task description. If you don’t know what they mean, the following few lines can help you understand.

As part of the month-end closing process, it is always necessary to make numerous manual postings in the financial accounting. Posting in accounting is when the balances in sub-ledgers and the general journal are shifted into the general ledger. Posting only transfers the total balance in a sub-ledger into the general ledger, not the individual transactions in the sub-ledger. In other words, after you enter, review, and approve transactions, you must post them to update your systems with current transaction records and maintain system integrity.

What is an SCD?

SCD stands for Slowly Changing Dimension, and is essentially a data structure that allows us to keep track of changes in our data.

What does “data change” mean?

In the world of IT, we typically store data in relational and non-relational databases. In this article, we start with relational databases, which are typically stored in SQL databases. Data entry is usually done through some kind of application where users input data using a desktop or sometimes some mobile device. No matter how, but the data eventually ends up in a data table. Consider a typical transaction: a sale event occurs and the following data (also called a record in a database language), that is, records are created

A data changes occur when a change, modification or deletion occurs in the already created and stored data (in this case the data above). SCD types are intended to symbolize the handling of the above changes.

More info on SCD:
https://www.datawarehouse4u.info/SCD-Slowly-Changing-Dimensions.html

https://www.allthingssql.com/slowly-changing-dimension-types/

Slowly changing dimension – Wikipedia

For example, SCD0 means that no changes are allowed to the previous data – (in practice, this is how transactions are stored in Block chain technologies, where you cannot delete or modify previous transaction data).

SCD1 is when we pass all changes to the current data file and do not store anywhere what data was stored before. Technically, SCD1 can already be considered a historization.

In this post, we show one of the benefits of SCD2 and how this type of historization can be used to create appropriate monthly posting files or a proper interface for accounting. You can read more about SCD2 and the different SCD formats following the links above

The task: Create a posting file with retroactive – aka. closed periods adjusting

Let’s suppose our company builds a calculation engine (hereinafter: the engine) in a database that receives transaction data from an application and then recalculates the transaction values from the received transaction data each time it runs.

( It doesn’t matter if this is a separate database, a database schema, or part of a transaction system to be developed, this solution is feasible in any case. I will now describe a solution where the transaction data is transferred using ETL processes to another database, and some of the calculations take place there, not in the application itself )

Several transformations can occur in the database that do not happen on the application side, e.g. Exchange rate assignment, assignment of partner data, product info, even purchase data, purchase prices, etc. On every run the engine receives the data from the application and from all other source systems and completely re-calculates the output data.

In our case, it is also the job of the engine to produce a posting file (or an interface) for the accounting program at an unspecified time at the beginning of each month. This part of the process is done manually, there is no automated running and data extraction

The Challenge

The engine completely recalculates everything on each run – clears the entire table contents at the database level (TRUNCATE) and loads the calculated data completely (INSERT).

Posting, on the other hand, occurs once a month at an unspecified time, during which only a portion of the calculated data (typically data for the previous month) is loaded into the accounting software (or ERP), based on a predefined field containing the transaction date.

The business analysis revealed that some transaction data may change even months after the first recording (UPDATE).

We did not receive any information regarding the possibility of data deletion during the development, however, it cannot be completely ruled out from the engine’s point of view

So to sum up the problem: how can we ensure the consistency of the calculated current data and the accounting data at the analytical level in the long run?

Let’s see our Example:

The transaction system will be launched in January 2022, and will be showing the following transactions when they are imported on the 2nd of February:

On the 3rd or March 2022 (the time of the next monthly posting/import) the whole transaction data set will look like this:

During the import on 3rd of March 2022, according to the protocol, only the data with the February TransactionDate (aka. PostingDate) will be loaded into the accounting system, however, we can see in the example that the data line (record) with the ID 3 has been deleted and for the record with Id 2, the Quantity was changed from 50 to 48.

The Alternatives

During the posting (in the posting file), we can follow the general cancellation rules, ie we make a change by adding the value of the previously recorded transaction with a negative sign (we can also post a canceled transaction in this way), and then re-enter the value and data of the correct transaction.

If the accounting software or ERP allows it, it is advisable to record the fact of the cancellation, and to record the ID linking the posted item to the original transaction together with the accounting item. (In our case there are two options: it is logical to use an ID field for this, however, if for some reason this field is not available, the InvoiceNumber and ItemNo lines can clearly identify a record, so we could use those as well).

A possible solution would be if the accounting system would always receive the full calculation, but this would cause a lot of data redundancy that would only make data reconciliation between the accounting and the engine even more difficult.

So keep in mind to make it as easy as possible to reconcile the differences.

The Solution: Historization and SCD2 helps!

First of all, we introduce historization into the engine in at least SCD2 format. During historization, it is sufficient to historize the final table containing each calculation step.

Historization – illustrated with data below – is done by introducing 2 Flag fields as well as two date fields, a DAT_FROM and a DAT_TO field, which show the validity period of the given transaction record.

The two flags are FLG_IS_CURRENT and FLG_IS_DELETED. Flags are managed as Bits, so they can only take a value of 0 or 1, 0 is false and 1 is true. (This form of SCD2 is just an option, no obligation for the data types, nor for the column names, etc. Try to grasp only it’s logic, if you are not familiar with it.

For the historization you will need to select the key field or key fields, using which the items can be clearly identified. These key fields determine whether an item was previously included in the data or not, and the modification steps are also performed based on these key fields.

When entering the system the current data will get the current date / time in the DAT_FROM field, the value of FLG_IS_CURRENT will be 1, the value of FLG_IS_DELETED = 0, and the value of the DAT_TO field will either be empty, ie NULL or e.g. 2999-12-31.

(I suggest a preferably high default value for the DAT_TO field, because NULL’s are mostly incomparable in rdbms systems.)

If an item is deleted, FLG_IS_CURRENT will be 0, FLG_IS_DELETED will be 1, and the DAT_TO value field will be updated to the time of the change.

If modified, the value of the FLG_IS_CURRENT field for the modified record changes to 0, and the value of DAT_TO changes to the time the change is registered (when the modified field is historized), and the field with new values is entered as the current new value in the historized table.

It is a good idea to store the current and historical tables in separate tables.

In the above case the HISTORY table would look like this on the 3rd of March 2022:

We can see that both items from January, which were modified, were modified in February, after the date of the last dispatch/import (February 2)

Preparing for posting/import

In order to be able to correct the posting with previously deleted or modified items, whether we export them manually or automatically for posting, we must record the date of the export. Let’s call this the DateOfExport parameter.

It is advisable to organize the actual solution by supplementing the record files containing the current transactions together with the plus sets needed for the corrections (and providing the sets with the appropriate signs), which can be handled to perform all the modification and transformation steps in the engine together which helps to produce the posting file.

The following figure will help you understand which sets to add to the current one for this purpose:

Explanation:

The blue and red areas are the ones that output the entire dataset that needs to be transformed.
The blue areas are the ones that are counted with their original sign, the red ones are calculated with the opposite sign.
It can be seen that only part of the entire ACTUAL file, is exported. The export is based on the original PostingDate field of the transaction data, that is, when the transaction was created.
The @LastDateOfExport is the date when previous month’s data was exported.
In addition to the current monthly data of the current record file, we need to add three sets of data:
- Deleted records: Records for which the following conditions are true in the historized table (each condition must be met, i.e. there is an “and” relationship between the conditions):
  - FLG_IS_CURRENT = 0
  - FLG_IS_DELETED = 1
  - DAT_TO › @LastDateOfExport – this guarantees that items that have been deleted AFTER a previous export will now be entered with a negative sign in the record set before the transformation.
- Historical data for modified records with a negative (opposite) sign: these are the records for which the following conditions are true in the historized table (each condition must be met, so there is an “and” relationship between the conditions):
  - FLG_IS_CURRENT = 0
  - FLG_IS_DELETED = 0
  - the value of @LastDateOfExport is between the DAT_FROM and DAT_TO records
- Current data of modified records: all records from the entire current set whose identifiers are included in the records defined in set 2. These are not duplications because they only contain records that were already current in a previous post, but their DAT_TO is greater than their @LastDateOfExport. The sign of the values of the present set is not changed.
One important modification: for all non-current records, the PostingDate value, ie the date value based on which it is selected for the given monthly post export, is changed to DAT_TO, thus guaranteeing that the added sets are included in the actual post file

The base record set generated this way:

We handle the above sets as a single input and we perform the transformations that are required for the sets to be accepted by the accounting software or ERP.

This blog entry does not cover this topic because these transformation are all target system specific and do not affect the data set and historization operations described above.

Benefits of this approach vs. other approaches

We don’t do a complete data file load into the accounting software or ERP system every time we do a posting. We do not burden the accounting systems with unnecessary records, simplifying the reconciliation.
We ensure continuous matching at the analytical level between the accounting software / ERP system and the reports showing the current data (eg towards partners)
We facilitates analytical reconciliations — especially when IDs are included in the posting file so that cancellation events (items recorded with the opposite sign) can be marked separately. This also facilitates coordination with partners and monthly and annual closing tasks.
We can also use this in case of automated connection. The only task is to store the DateOfExport value (recordeed manually in the present case study) in the “engine” after the successful posting.
We cover almost every possible business need creating a robust solution that is prepared for future requests. For example, even if initially there has been no demand to manage cancellations, if such requirement may arise later the engine will be prepared for this

Just one last thing:

Our Rapid solutions (Rapid Planning and Rapid Analytics) provide the ability to use all of the slowly change data management methodologies at the data warehouse level, so our company and our clients can easily create data market solutions supplemented with historization, based on which “time-machine” tabular models can be created. For example our datawarehouse automation solution (Rapid Analytics) is ideal for default historicization solutions

Thank you for your time! I hope you liked my post and found it useful. If you have any comments, additions or questions feel free to contact me at kreiszzs@abylon.hu

The post How to post G/L records with retroactive data with the help of BI and SCD? appeared first on Abylon.

Internal financial planning solution for SSC-s

Zoltán Zicherman — Mon, 30 Aug 2021 15:51:38 +0000

Occasionally, there is a new solution or innovative technology, which claims to be the new “wow”, the new “jolly joker” solution, that will solve ANY or even ALL Information Technology/Business/etc. difficulties your company is facing right now. Let’s get this straight!

Today, you are not going to read about the universal “next big thing”, but if you stick around, you’ll get to know a super practical tool that can significantly improve your current way of doing financial planning, budgeting, controlling, and forecasting.

Let’s see, what Abylon Rapid Planning is not:

It’s not a magic tool. It’s a technology-based solution, with its own pros and cons.
It’s not for everybody. It’s not designed for small companies. To put it simply, it’s not cost effective enough for them to implement such a solution.
It doesn’t fit every need. If you are looking for an application with a super-fancy, website-like front-end, you will be disappointed. Our solution’s front-end is basically just an extension on top of Excel. Funny thing, but actually that’s one of its main and best features, since users don’t need to learn everything from scratch and don’t have to spend extra money on front-end – if you have Office365 (nowadays Microsoft365), You already have your front-end.
It’s not a “real time” solution: because it shouldn’t be. If you’ve ever used Excel in safe mode, you know how annoying it is when errors pop-up constantly. With Abylon Rapid Planning – you type in your data, and if you think it’s OK, you’ll send it. That’s it. No errors, no nothing.

Before we go on, I must say I genuinely believe everyone is doing their best with what they have – so I did not mean to offend anyone (I hope I didn’t).

Understanding the problem (based on personal experience)

Let me tell you a quick story of what happened when I worked at a Hungarian subsidiary of a big banking company – a subsidiary was basically operating as an SSC. The main business of the subsidiary was – and probably still is – to provide administration services to all the other subsidiaries of this multinational bank around the globe.

What exactly did we do?

The office where I worked did month-end closings using mainly Excel. Therefore, most people working there needed Excel experience and some sort of financial background. We downloaded some data, made the closing registries in Excel or in a separate program, and then all the numbers got uploaded and consolidated somehow.

I was part of the business development team, trying to automate tasks with VBA (Visual Basic Application). After a lot of effort, my colleague managed to upload the data (the entries made in Excel) into an SQL database through VBA. That was quite a result, but still not good enough. So, what was the problem you may ask?

The problems with this approach and solution were the following:

There was only one person who had the required VBA knowledge. If he leaves or just gets sick for a longer period, they couldn’t replace him.
VBA is deprecated by Microsoft, which means that even Microsoft won’t support it, and no further developments are supported.
VBA is also called “shadow-IT”. In other words, any custom application developed with VBA won’t have any support from the internal IT team.
The result was only HALF of the original project, since the solution wasn’t able to get the data, everyone needed, data was still distributed and downloaded manually, and all the transformations were also made in Excel.

Simplified financial planning, budgeting and forecasting

What if I told you that right now there is a product on the market which can solve all these problems? Furthermore, if you have people with some SQL knowledge – for example there is an in-house Business Intelligence (BI) team – which is quite standard today, you will be able to develop and customize your solutions further anytime when there is a new business requirement.

The only things you will need:

Some business expertise
Excel knowledge
and SQL knowledge

If you have these, with Abylon Rapid Planning you will be able to build robust, exceptionally reliable, customizable solutions based on Excel templates developed by your own team.

Why do I believe this is a game changer for SSC-s? Or even most enterprises who have accounting, controlling, and planning procedures, or provide these activities for other companies, or subsidiaries?

Because I’ve seen a lot of real-life examples of these Excel-based procedures at various companies. I’m talking about downloading data manually, transforming it manually then sending the Excel files in emails approach. These “workflows” could’ve been transformed to something smooth, more automated, and more focused on providing genuine business value kind of processes. Processes which are also easy to scale, support and develop further anytime the organization or the workflow requires.

For more information on Rapid Planning check the product page following the link below or contact us to schedule on online demonstration.

The post Internal financial planning solution for SSC-s appeared first on Abylon.

Rapid Platform – Abylon

Five Biggest Challenges in Financial Planning

Intro

1 - Manual consolidation of Excel files

2 - Resistance to New Planning Tools

3 - Challenges in Tracking Progress

4 - Your experts doing avoidable tasks

5 - Data Quality issues

The Paramount Issue: Time

Why Our FP&A Solution Stands Out?

Our Financial Planning Solution

Our Philosophy

The Ultimate Value of Financial Planning

More on Financial Planning and Analysis

Author of the post:

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Automated SQL Data Warehouse project done in 3 weeks with minimal prior experience

Data warehouse implementation - easier than expected

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Effective Master Data Management with the Abylon Rapid Platform

Effective Master Data Management with the Abylon Rapid Platform

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Use case I. - Basic categorization

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How to post G/L records with retroactive data with the help of BI and SCD?

For whom this blogpost is meant for

Intro

What is posting in accounting?

What is an SCD?

What does “data change” mean?

The task: Create a posting file with retroactive – aka. closed periods adjusting

The Challenge

The Alternatives

The Solution: Historization and SCD2 helps!