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⏳Today’s reading time: 4 minutes
Here’s what’s brewing in the data world:
1️⃣ Looker is making an appearance in the AWS multiverse
2️⃣ Power BI has announced its latest release and some major updates to its modelling experience!
3️⃣ Thoughtspot has introduced Analyst studio which offers data engineering & data science experiences with SQL and Python
4️⃣Sigma has launched Ask Sigma, its Natural Language Query (think AI in BI) offering
Business Intelligence 💡📊
Looker
What is it: Looker (Google’s BI platform), is now available in AWS marketplace. This gives AWS customers the flexibility to choose their preferred BI analytics platform for the "last mile" of their data journey. Looker joins the likes of Qlik Sense and Spotfire, in the marketplace, offering an alternative stack to those looking beyond Amazon’s own BI platform - Quicksight.
AWS Marketplace also provides the convenience of procuring Looker directly from Marketplace, by offering billing management within the AWS environment.
Source: AWS
Why is it relevant: Vendor lock-in is still a real headache for a lot of businesses, especially when the bills start piling up as they scale their data operations. With Looker now in the AWS Marketplace, companies can avoid being stuck with just one cloud provider. It’s a win for those looking for a Multi-Cloud setup—and it’s also a smart move for Looker, expanding beyond Google to capture more growth.
Check everything out here.
Microsoft
What is it: Microsoft just dropped its latest Power BI update, and there are two features grabbing a lot of attention. First, versioning for Semantic models (datasets) in the Power BI service is now a thing! This is a huge win for maintaining data integrity and ensuring you can roll back any accidental changes. Second, TMDL Scripting (pronounce it however you like—Timdl or T-M-D-L) is now in preview for Power BI Desktop. For all the pro devs out there, TMDL gives you fine-grained control over semantic model objects like tables and measures, making it easier to reuse objects and integrate with CI/CD pipelines. If you want to nerd out, here’s a detailed video:
Why is it relevant: Being able to edit datasets directly in Power BI service with versioning is a game changer for business developers—it’ll help keep things in check and make sure nothing gets accidentally messed up. Plus, TMDL is a powerful feature that opens the door for pro developers to integrate more tightly with Git and improve their workflows.
That said, keep in mind these features are still in preview, so there are some limitations to work around for now. You can read the entire monthly release here.
Thoughtspot
What is it: Thoughtspot has launched Analytics Studio, bringing new features like the ability to create datasets with a SQL editor and adding Python & R support in notebooks. With these expanded capabilities, it looks like Thoughtspot is really aiming this release at analysts.
Source: Thoughtspot
Why is it relevant: BI tools are all competing to win over users, each focusing on different needs. Thoughtspot’s new features seem designed to keep data analysts in the platform for their day-to-day work—no need to jump between tools higher up the data value chain. However, the documentation around CI/CD and metadata management is a bit murky, so it’ll be interesting to see how well these features are actually received.
Read all about it here
Sigma
What is it: While Sigma’s product launch dropped in December, the company also introduced Ask Sigma, its AI in BI offering. With Ask Sigma, the focus seems to be on transparency and control.
Source: Sigma
Transparency comes in the form of a detailed breakdown of each step the tool takes to answer a natural language query. Users can see exactly what’s happening behind the scenes. Control is built in by letting you edit the steps taken during the process—whether it’s filters applied or custom calculations made. Plus, if you want to dig deeper, you can take the analysis from Ask Sigma and jump back into the main experience in the home view for more customization.
Why is it relevant: AI in BI is still a tough sell, especially because execs often struggle with the lack of transparency in AI models. Sigma is tackling this head-on by giving users visibility into how their results are generated and offering more control over the process. It's a big step toward making AI in BI more user-friendly and trustworthy.
Read all about it here
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