Frequently asked questions

Here, we will answer all the questions you have about the different plaftorms we use. Are there any questions left unanswered? Feel free to submit them here:

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PLainsight

Plainsight pictogram 
What makes Plainsight different from traditional data consulting firms?

Plainsight is different from traditional consulting firms due to its open knowledge sharing (of which playbook.plainsight.pro is an example), the templated solution accelerators and it’s co-creation with customers.  

What types of organizations work with Plainsight?

Plainsight’s customer base is diverse, spanning large international enterprises with thousands of employees, niche boutique SaaS firms managing high volumes of data, and medium-sized traditional businesses taking their first steps into data, analytics, and AI. Most of Plainsight’s customers operate within the Microsoft ecosystem, leveraging tools such as Power BI, Azure, and Microsoft 365, and in more advanced scenarios, Databricks to support their data and AI ambitions. 

How does Plainsight turn data into business value

We combine a thoughtful, human-centered approach with clear communication and reliable results. It’s not just what we do—it’s how we do it that sets us apart.

Microsoft fabric

  • Microsoft Fabric is an end-to-end cloud data and analytics platform that unifies data engineering, warehousing, real-time analytics and BI in one environment.

  • Yes. Microsoft Fabric runs on Azure cloud infrastructure, but is delivered as a fully managed service via the Microsoft 365 / Power BI tenant.

  • Microsoft Fabric is SaaS: it delivers a fully managed analytics experience in the browser without managing infrastructure or clusters yourself.

  • Power BI is relatively easy to learn for Excel users, but advanced modelling and DAX formulas have a learning curve.

  • Fabric is a SaaS lakehouse tightly integrated with Microsoft 365/Power BI. Databricks is a PaaS lakehouse on Spark with more engineering/AI flexibility and less opinionated integration.

  • Fabric offers a free trial and limited free capacities (F SKUs) for testing/low-scale; production use typically requires paid capacity (Premium / F Premium SKUs or Pro licenses for sharing).

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Databricks

  • Databricks works as an integrated data and AI platform (lakehouse) built on Apache Spark. It enables ingest, processing, analytics and machine learning in one managed environment with clusters and notebooks.

  • Databricks pricing depends on usage. You pay for compute, storage and features. Light workloads can be cheap while large ETL or AI pipelines can become expensive.

  • No. Databricks is a lakehouse for data and AI on Spark; Snowflake is a cloud data warehouse for SQL-based storage and querying. They overlap but have different primary focus.

  • Databricks is primarily a PaaS (platform as a service) with a SaaS-like UI and managed services delivered in the browser.

  • The platform itself is not fully open source, but it is built on and maintains major open-source projects such as Apache Spark, Delta Lake and MLflow.

  • Yes. Databricks is a unified data and AI platform (lakehouse) for ingestion, engineering, analytics, streaming and machine learning in one environment.

  • Choosing between Microsoft Fabric and Databricks is depends on factors such as technical knowledge of your team (SQL, Python, …), multi-cloud strategy, SAP dependability and reporting tools (such as Power BI). Both tools have a completely different costing structure (pay per use for Databricks compared to Fabric Capacity Units) and it is therefore advised to contact Plainsight for guidance in this decision.   

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Power Bi

  • Power BI is a Microsoft data analytics and dashboarding platform used to visualize, model and share data.

  • Power BI connects to data sources, transforms and models the data, and presents it through interactive reports and dashboards in desktop or web.

  • Power BI has a free desktop version. Power BI Pro is licensed per user per month, and Power BI Premium offers capacity-based pricing for larger organizations.

  • Power BI is relatively easy to learn for Excel users, but advanced modelling and DAX formulas have a learning curve.

  • Power BI delivers fast visual insights, integrates with Microsoft 365, supports DAX modelling and simplifies sharing dashboards in the cloud.

  • Power BI is built for scalable data models, scheduled refresh, governance and interactive dashboards, while Excel is better suited for ad-hoc analysis.

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