12 September 2022 Boost e-commerce growth with automated data management Share this message The COVID-19 pandemic has had a devastating effect on economies worldwide. Simply put, it forced businesses to reconsider the way they market and sell in order to stay competitive. As a result of several lockdowns and stay-at-home orders, consumer needs evolved, and buying moved largely to online purchasing models. This led to a surge in e-commerce, a trend that is expected to continue in the foreseeable future. The question is: How e-commerce retailers can ensure growth and scale their businesses in light of this increased demand? The simple answer lies in data. In this white paper, we’ll look at the role of data in e-commerce and the solutions retailers can implement to ensure continued growth. Fill out the form on the right to receive your free copy. Want to know more about TimeXtender? TimeXtender is an automated data management platform that helps implement and operate data lakes, data warehouses, and data marts – without writing code – automating the process of getting data ready for analysis. By implementing a Modern Data Estate with TimeXtender, you can spend less time building, and more time focused on making better business decisions backed by your organization’s data, mind, and heart. Because Time Matters. More from the Bitmetric team Bitmetric Qlik Support Keep your Qlik environment running smoothly with proactive support that prevents issues before they appear. Available on flexible monthly plans. Learn more. Qlik vs Power BI Series See how Qlik and Power BI perform when theory meets reality. Three apps rebuilt, every step examined. Learn more. E-book E-commerce TimeXtender How can we help? Whether something’s still unclear or you’re ready to take the next step, Barry and Eric are happy to talk it through. Email us, call us, or book a meeting at a time that works for you. Call us Mail us 1 September 2026 Qlik Answers review: What we learned from real-world testing We tested Qlik Answers on a real production sales model to see how it handles real-world analytics. The results were promising, but getting reliable answers required careful work on the logical model, master measures, dimensions and business context. AI Data Analysis Qlik Semantic Layer 25 August 2026 Your semantic layer is becoming the API for AI Semantic layers are not new, but AI is giving them a new role. Where they once primarily powered dashboards, semantic models are increasingly becoming the layer that provides AI with reliable business context. AI Data Governance Microsoft Fabric Qlik Semantic Layer TimeXtender 17 August 2026 Putting AI to work on your data works. But not like this. Putting AI to work on your data sounds simple. But what can we learn from organizations already doing it? Based on Anthropic’s experience and independent research: what works, what doesn’t, and why maintenance is where the real work lies. AI Data Governance Data Management Power BI Qlik
1 September 2026 Qlik Answers review: What we learned from real-world testing We tested Qlik Answers on a real production sales model to see how it handles real-world analytics. The results were promising, but getting reliable answers required careful work on the logical model, master measures, dimensions and business context. AI Data Analysis Qlik Semantic Layer
25 August 2026 Your semantic layer is becoming the API for AI Semantic layers are not new, but AI is giving them a new role. Where they once primarily powered dashboards, semantic models are increasingly becoming the layer that provides AI with reliable business context. AI Data Governance Microsoft Fabric Qlik Semantic Layer TimeXtender
17 August 2026 Putting AI to work on your data works. But not like this. Putting AI to work on your data sounds simple. But what can we learn from organizations already doing it? Based on Anthropic’s experience and independent research: what works, what doesn’t, and why maintenance is where the real work lies. AI Data Governance Data Management Power BI Qlik