Lenses Community Edition | Getting started
Lenses Community Edition is a completely free Kafka tool to blaze your path to production with data streams.
Using Set Analysis P() to Improve Your Marketing Spend
On the Next Do More with Qlik Tips and Tricks edition: Using Set Analysis P() to improve your marketing spend. By focusing only on those customers tied to key product purchases, you can better analyze what’s driving real revenue—and adjust your marketing budget accordingly. Target smarter, spend better.
Breaking down enterprise data silos with Moin Haque
How do enterprise leaders navigate fractured data landscapes and integrate AI into business strategies? On this episode of The Fivetran Data Podcast, Moin Haque, Head of Enterprise Data, Analytics & AI at International Flavors and Fragrances Inc. (IFF), shares actionable insights into data federation and innovation with host Kelly Kohlleffel. Key highlights.
Guardrails for growth: Leadership and governance in AI implementation
The Head of Enterprise Data, Analytics & AI at IFF sat down with Fivetran to unpack how to successfully implement AI while balancing both innovation and governance concerns.
Shifting Left: How Data Contracts Underpin People, Processes, and Technology
The divide between operational and analytical systems has long resulted in data inconsistencies, unreliability, and redundancies. Without a single, unified source of truth, teams interpret information in their own ways—often after the fact. This can lead to downstream data discrepancies, issues, and distrust. Meanwhile, changes to upstream data structures create ripple effects, breaking downstream systems and requiring manual intervention to fix issues.
12 Best SQL Server ETL Best Practices
In a world where data-driven decisions shape the future of every business, ETL (Extract, Transform, Load) processes are the backbone of operational intelligence. For organizations using Microsoft SQL Server, optimizing ETL pipelines isn't just a technical choice—it’s a strategic imperative. With over two decades in the ETL trenches, I’ve seen what works, what fails, and what silently erodes performance behind the scenes.
Key Takeaways from Accelerate: How Financial Services and Manufacturing Companies Leverage Data and AI for Measurable ROI
For many organizations across industries, the era of experimental AI has given way to the era of practical implementation. Even those companies still testing and evaluating AI solutions are shifting away from the art of the possible to focus more closely on what will soon produce measurable ROI. “It will no longer be enough for your organization to merely use AI to win the approval of company leadership,” says Samuel Lee, Product Marketing Director for Financial Services at Snowflake.
The Apache Iceberg Avalanche: How the Open Table Format Changes the Face of Data Lakes
Data storage has been evolving, from databases to data warehouses and expansive data lakes, with each architecture responding to different business and data needs. Traditional databases excelled at structured data and transactional workloads but struggled with performance at scale as data volumes grew. The data warehouse solved for performance and scale but, much like the databases that preceded it, relied on proprietary formats to build vertically integrated systems.
Accelerate analytics with AI-assisted data preparation in BigQuery, now GA
BigQuery data preparation is generally available and integrates with BigQuery pipelines and BigQuery repositories and Git.
Risk & Reward: A Balancing Act for Success
Adopting AI? Risky. Not adopting AI? Riskier… It’s an interesting conundrum illustrating a broader truth: playing it safe is sometimes risky. To succeed, companies need to take smart risks—and those who do often achieve the greatest rewards. But a risk that is smart for one organization may not be as smart for another, so what risk is right for you?