BI has accelerated dramatically changed the recent years

Are you somewhat bewildered by the constantly changing landscape of Enterprise IT?

For years the business intelligence domain has been centered around On-premise SQL servers, OLAP cubes and ETL processes. With more than 30 years of calibration and best practice generation, the foundation has been rock solid, and most Business Intelligence consultants have easily been able to identify and adapt to small changes in frameworks and technology.

Constant adaptation is the new normal, and something IT organizations need to embrace more than ever before. Recent years, new technological advancement within cloud computing, big data, and the unfolding of the AI-potential, has gradually pushed the development in new directions.

Even the mastodonts of cloud computing: e.g., AWS, Azure and GCP seem to be somewhat ambiguous about the strategic directions and hence also the positions of the architectural frameworks in their service offerings.

Discontinuing obsolete technologies that are well adapted in the global business landscape is an immense challenge, but nonetheless an important decision in catering to future needs. However, keeping a business running stable while adapting to all the changes can be really challenging.

As a business intelligence consultancy with professional presence since the very beginning, it appears that these changes have being accelerating dramatically. In 2022-2023 for instance, we have already seen multiple substantial changes in the Microsoft Power Platform offerings, that for good reason, makes executive decision makers scratch their heads.

Right now, you may be considering several BI-related options that could be detrimental to your competitive advantage and the operational cost of running a BI solution.

  • Is it advisable to transition to cloud right now, or could you as well wait a few years with your standalone SQL Server environment?
  • Should you rely on Serverless. SQL pools or a combination when you choose your architecture, and what do you need to understand in terms of costing?
  • If you are opting for D365, what are the benefits of using an Entity or Table specific data export layer?
  • Should you consider jumping the train from the get-go with Microsoft Fabric?

If you are puzzled with one or more of the above topics, please consider reaching out to have an unformal talk about your options.

In the following article “Should you go with SASS cubes or models built directly in Power BI”, we will scratch the surface and bring our view to the board with regards to some aspects to the questions framed above.



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