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Qlik and Agentic AI in 2026: What’s New, What’s Real, and What to Watch Next

“What were sales last quarter?” Business users increasingly expect: > “What changed, why, what should we do next, and can you open the ticket / notify the team / update the forecast?” Agent-like experiences require more than NLQ (natural language querying). They require: Context (business definitions, KPI logic) Trust (lineage, governance, quality signals) Workflow integration […]

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Hugging Face in Practice: How to Use Models, Datasets, and Pipelines for Real‑World AI

Artificial Intelligence /

February 09, 2026 at 05:43 PM | Est. read time: 13 min By Valentina Vianna Community manager and producer of specialized marketing content Hugging Face is one of the most practical ecosystems for applied AI-especially when you want to move quickly from an idea to a working prototype, then into a production workflow. If you’ve

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Will AI Agents Replace Teams? What Actually Changes (and What Doesn’t)

Artificial Intelligence /

February 09, 2026 at 05:24 PM | Est. read time: 16 min By Valentina Vianna Community manager and producer of specialized marketing content AI agents are moving fast-from answering simple support tickets to drafting code, summarizing meetings, and orchestrating multi-step workflows across tools. It’s natural to wonder: will AI agents replace teams? In most real-world

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Microsoft Fabric, Explained: Architecture, Key Benefits, and Common Adoption Challenges (Plus How to Overcome Them)

Data Analytics /

February 06, 2026 at 02:42 PM | Est. read time: 18 min By Valentina Vianna Community manager and producer of specialized marketing content Microsoft Fabric is Microsoft’s end-to-end analytics platform designed to bring data engineering, data integration, data science, real-time analytics, and business intelligence into a single, cohesive experience. Instead of stitching together multiple products,

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Beyond Pretty Charts: Why Dashboards Often Fail to Drive Real Decisions (and How to Fix It)

Data Analytics /

February 06, 2026 at 01:21 PM | Est. read time: 13 min By Valentina Vianna Community manager and producer of specialized marketing content Dashboards are everywhere-BI tools, product analytics, sales reporting, ops command centers. Yet many teams share the same frustration: the dashboard exists, the numbers update, but decisions don’t change. If you’ve ever heard,

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Great Expectations for Data Quality: How to Build Trust From Your First Pipeline

Data Analytics /

= 0) Date bounds (e.g., created_at Notes: > – This example uses a Pandas DataFrame batch for readability (great for first implementations and many warehouse extracts). > – In production, you can point GX at your warehouse/lake (e.g., via SQLAlchemy, Spark) using the same expectation concepts. 1) Define an Expectation Suite (GX 1.0-style example) `python

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Build vs. Buy in Data Platforms: When to Develop In‑House vs. When to Outsource

IT Outsourcing /

February 04, 2026 at 01:00 PM | Est. read time: 18 min By Valentina Vianna Community manager and producer of specialized marketing content Build vs buy data platform decisions come down to two forces: time-to-value and long-term differentiation. If you need trusted metrics fast, buying (and selectively outsourcing) gets you there. If the platform itself

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dbt: Transforming Data with Governance and Version Control (Without Slowing Teams Down)

Data Science /

February 03, 2026 at 02:18 PM | Est. read time: 11 min By Valentina Vianna Community manager and producer of specialized marketing content Modern analytics teams are expected to deliver trusted, “always-on” data-fast. But speed without consistency creates a familiar mess: conflicting definitions, undocumented logic, broken dashboards, and a growing lack of confidence in reporting.

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How to Build a Data Roadmap Aligned With Business Strategy (A Practical, Step-by-Step Guide)

Data Analytics /

February 03, 2026 at 02:23 PM | Est. read time: 12 min By Valentina Vianna Community manager and producer of specialized marketing content A data roadmap is only “successful” if it moves the business forward-not if it simply lists tools to buy, dashboards to build, or platforms to migrate. When organizations treat a data roadmap

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Modern Data Architecture for Business Leaders: What It Is, What’s Changed, and What to Do Next

Data Engineering /

January 29, 2026 at 04:30 PM | Est. read time: 15 min By Valentina Vianna Community manager and producer of specialized marketing content Modern data architecture isn’t just an IT topic-it increasingly shapes speed to market, customer experience, operational efficiency, and compliance risk. The way your company collects, governs, shares, and uses data determines whether

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