To view just the slides from this presentation, click HERE>> This webinar is sponsored by: About the Webinar Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need. There are so many Data Architecture best practices today, accumulated from […]
ADV Slides: Data Architecture Best Practices for Advanced Analytics
To view the on-demand recording from this presentation, click HERE>> This webinar is sponsored by: About the Webinar Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need. There are so many Data Architecture best practices today, accumulated from years […]
A Beginner’s Guide to Data Modeling and Analytics
As more and more companies start to use data-related applications to manage their huge assets of data, the concepts of data modeling and analytics are becoming increasingly important. While they typically rely on one each, they are two very distinct concepts. Companies use data analysis to clean, transform, and model their sets of data, whereas they […]
Digital Transformation Best Practices
The term “digital transformation” (DT) encompasses the holistic framework and the associated strategy designed for integrating technology, business processes, and employee effort to get the maximum value for business customers. In a digitized business model, the “customer journey” is the central focus. While creating the DT framework, the business operators develop business models that are […]
Databases vs. Hadoop vs. Cloud Storage
How can an organization thrive in the 2020s, a changing and confusing time with significant Data Management demands and platform options such as data warehouses, Hadoop, and the cloud? Trying to save money by bandaging and using the same old Data Architecture ends up pushing data uphill, making it harder to use. Rethinking data usage, storage, and computation is […]
Data Science vs. Data Analytics
The data scientist and the data analyst represented two of the “most in-demand, high-paying jobs in 2021.” The previous year, the World Economic Forum Future of Jobs Report 2020 listed these jobs at the top of a list representing most in-demand jobs across industries. In data analytics, which is often referred to as business analytics, […]
Building Analytics for External Users Is a Whole Different Animal
Analytics aren’t just for internal stakeholders anymore. If you’re building an analytics application for customers, then you’re probably wondering: What’s the right database backend? Your natural instinct might be to use what you know, like PostgreSQL or MySQL or even extend a data warehouse beyond its core BI dashboards and reports. But analytics for external […]
What You Don’t Know About Real-Time Data Is Killing You
One of the biggest pitfalls companies can run into when establishing or expanding a data science and analytics program is the tendency to purchase the coolest, fastest tools for managing data analytics processes and workflows, without fully considering how the organization will use these tools. The problem is that companies can spend much more money […]
Exploring Data Visualization in Three Steps
Data analytics has accompanied me for 15 years already. I started my career as a data analyst in a controlling department immediately following my graduation from the University of West Bohemia; I now work as a data scientist providing consultancy services for a range of different fields. The data analysis itself is the fun part. […]
Webinar: Data Pipelines Without the Headache – How Accessibility and Affordability Enable Data Success
To view just the slides from this presentation, click HERE>> This webinar is sponsored by: About the Webinar Organizations understand the value in leveraging their data for improved BI, analytics, and reporting. However, utilizing data effectively requires sophisticated data integration, which to many organizations sounds like a trade-off that might not be worth the effort. […]