The Personal Data Stack of a Data Strategy Consultant
What are the tools you collect on your way?
As a consultant in Data & Analytics Strategy, I’m vendor independent. But I have also more than 15 years of history in building data solutions or data teams using different solutions.
My personal history is strongly around SAP (SAP BW, BusinessObjects BI, SAP HANA, …) , but earlier I had also times working with Data Science tools or had opportunities to work with other BI tools like WebFocus (Information Builders) or DeltaMaster (Bissantz). Later I built up consultants with the Microsoft Stack, like Power BI and MS SQL Server (ink. SSAS, SSIS, SSRS) and Data Science looking for Python- and R-based approaches and tools.
Today in strategy I’m not implementing anymore but facing a lot of different tools all the time. The best way to learn for me is to install it and try it out or access a cloud service e. g. a trial access or similar. As my emloyer is partnering with a lot of different vendors in the data & analytics realm, we host also larger systems or have access to different cloud services. So if I checked now my locally installed tools and the services I have access to and already tried out more or less, I came up with this:
Fig. 1: My Personal Data Stack
So for sure, this is a lot :-). But everything is there for a reason and we know the amount of data tools outside is huge. I also see much more on the customer side, but I think also it is not necessary to always try out the exact tool. It is more about getting a feeling how things work. And therefore working with at least two tools with similar functionality is really helpful.
As my history was SAP for a long time and I still work a lot with SAP colleagues, it makes sense from time to time to have a look inside to try something out or get a better picture about the latest features, especially for cloud solutions like SAP Analytics Cloud or SAP Datasphere. These both are currently the strategic solutions for Data & Analytics at SAP:
Fig. 2: SAP Datasphere - SAP’s Data Fabric and Data Warehouse solution and SAP Analytics Cloud als Planning and Analytics solutions
But also the services and platform features available on the SAP Business Technology Platform and the SAP Business Applications Studio for all kinds of development incl. based on SAP HANA which is also part of SAP Datasphere on top.
Fig. 3: SAP Business Application Studio and SAP Business Technologie Platform as SAP’s Platform-as-a-Service (PaaS) offering
But I still having the possibility to look into SAP BW or SAP ERP, which can make sense sometimes.
We work with all the Hyperscaler like Google Cloud or Amazon Web Services but Microsoft Azure has for sure the largest foodprint and has typically a good fit in customers cloud and Microsoft strategy with MS Office 365, SharePoint, Power Apps and Teams. It comes often with Databricks and Power BI on the customer side.
Fig. 4: Microsoft Azure Portal (hier with Azure Data Factory) and Power BI Desktop
GenAI and Machine Learning is a hot topic today. While I didn’t put GenAI in the overview for sure it plays a role but more in the consulting context. You can easily try out different services like ChatGPT (OpenAI), Gemini (Google), Claude.ai (Antrophic) or going more experimental on HuggingFace. Low Code tools like KNIME or Dataiku also adapted GenAI to integrate models into their workflows. These tools are also helpful to handle the full data preparation workflow and connect different tools - from source to data platform to be able to do machine learning and visualization or integrate necessary functions as needed. I also had my phase in programming, especially when I tried to update my Data Science skills several years ago, learning about Deep Learning, R, Python, Anaconda for providing Jupyter Notebook and Jupyther Lab and managing Python and R environments, and so on.
Fig. 5: Data Science Solutions - KNIME & Dataiku and Googles Colab as a Notbook-oriented solution
For sure it makes sometimes things easier to have a local database and PostgreSQL is very common for a lot of customers, too. I also once installend MariaDB but just played a little bit around. And than you need tools to handle the database like HeidiSQL or DBeaver, which can connect to different databases helping you to manage some SQL and ad-hoc actions with your database.
Starting at INFOMOTION I came in touch with Data Catalogs, what wasn’t a topic before for me. Currently we are partnering with Collibra and Alation as Enterprise Data Catalog solutions, but always have a look on other solutions like Collate (Open Metadata), Azure Purview or others. Today Data Catalog are hot to foster data transparency and enable data democratization. But they can also be important in compliance cases and support data governance. Though, it is not easy and often underestimated to implement such a solution.
Fig. 6: Data Catalog solutions - Alation & Collibra
Analytics tools like Power BI or Tableau are widely spread and we internaly use Power BI for our own reporting. We are also using IBM Cognos TM1 for planning but I hadn’t much practice on it. As already written, SAP Analytics Cloud and also SAP BusinessObjects BI (BO) is found at SAP customers and BO also a lot on customers where SAP plays not the same role due to the history of BO. I remember also I had once QlikView and Qlik Sense on my computer, but currently not.
So I assume I’m here in a special situation, having access and opportunities to try so many Data & Analytics tools. And I’m for sure not an expert in most of them. But to try out hands-on what tools are about and how things work, it is really helpful for me.
What is your Personal Data Stack? What is easy to try out for you? Do you regularly practice with it?