Introducing Native Spreadsheets in ThoughtSpot

Every analyst has been there: Deadline looming, data in hand, and a BI tool that either requires a workflow you haven't learned or a colleague you can't reach. So you open Excel. It's familiar, it's flexible, and it works right now. So that's where the work happens—and now where insight stays, ungoverned and invisible to your team, your analytics stack, and your agents.

Full Autonomy, Full Security: ClearML and SUSE k3k Bring Virtual Kubernetes Clusters to Enterprise AI

Kubernetes has become the de facto substrate for enterprise AI infrastructure. Its ability to handle complex, long-running workloads, self-healing capabilities, and rich ecosystem of GPU operators, storage drivers, and networking tools make it the natural platform for organizations scaling AI beyond the lab.

Build a Data Input App with Kai

This is a Data App that collects structured product submissions from a team, validates them, queues them for approval, and writes approved entries directly to a Keboola table. I built it with Kai in one conversation. No Google Sheets. No broken column headers. No emailing CSVs. If you've ever needed your team to submit structured data - new products, budget inputs, campaign briefs, vendor details - and the spreadsheet approach keeps falling apart, keep reading.

I Let AI Audit My LinkedIn Strategy (Here's what happened)

If you’re consistently posting on LinkedIn, the hard part isn’t getting data — it’s analyzing it. Most people review posts one by one, compare impressions manually, and try to “spot patterns” by eye. That’s slow. And it makes strategy reactive. In this walkthrough, Kamil Rextin, founder of 42 Agency, uses the Databox MCP with Claude to run a fast, AI-driven analysis of his LinkedIn performance — the kind of first-pass review you’d normally assign to a junior analyst.

Your Client's Growth Looks Good... But Is It Competitive?

Most agencies report on growth. But growth alone doesn’t answer the real question clients care about: Are we actually competitive? In this walkthrough, 42 Agency shows how they use the Databox MCP with Claude to benchmark client performance against relevant peer groups — filtered by size, revenue, and industry. Instead of relying on generic industry averages, they combine: The result? Stronger strategy conversations, clearer goal setting, and more confident planning grounded in a real market context.–

Cloudera Open Data Lakehouse: Seamless Data Management and AI #Cloudera #AI #Tech #Shorts

Modern enterprises are currently overwhelmed by massive, fast-moving data in various formats that traditional legacy warehouses simply cannot manage. Cloudera addresses these complexities with its open data lakehouse powered by Apache Iceberg, providing a single, seamless, and optimized view of all your information.

From Chaos to Clarity: How Spotter Unifies Healthcare Data for Better Decisions

Most healthcare teams are making decisions from multiple different dashboards and systems that don't talk to each other, which means someone is manually stitching together the picture—one that's always slightly out of date by the time it's ready. Outdated or incomplete data can lead to fragmented patient care and experiences. And no health system wants that. Whether tracking enrollment targets or auditing claims denials, Spotter applies standardized clinical logic to your unified dataset so you can focus on what matters: the patient. Go from chaos to clarity.

Lookup Mapping in Integrate io

Learn how to master lookup mapping in Integrate.io to enrich your data streams and build smarter, more powerful pipelines, no coding required. Lookup mapping lets you cross-reference records in real time during pipeline execution, so you can enrich incoming data with information from another source without pre-processing or heavy database joins.

SAP Data Migration and the 2027 Deadline: What Every Business Needs to Know Before It's Too Late

If your organization is still running SAP ECC, the clock is ticking. SAP has set 2027 as the end of mainstream maintenance for SAP ECC 6.0. This announcement means no more standard support, security patches, or bug fixes after that date. For large enterprises in manufacturing, food and beverage, pharma, chemicals, and logistics, the pressure to complete an S/4HANA migration before that deadline is becoming impossible to ignore. The risk isn’t just technical.

Three Finance AI Challenges Product Leaders Must Overcome

Product teams tasked with providing an AI analytics and BI platform to finance organizations see a unique set of challenges. Finance organizations are subject to SOX, GDPR, EU AI Act compliance on top of accurately closing the books and preparing for the potential of an audit. In a highly regulated industry like finance, product leaders building solutions for finance leaders need accurate insights they can trust that hold up to audits and regulatory scrutiny.