Data is an integral aspect of every organization across all industries. However, presenting data is a crucial exercise that requires a lot of creativity to ensure that every team member can grasp the meaning of the content. Many people get confused about how to find valuable insights from a large volume of data in a spreadsheet. That’s […]
What Can Artificial Intelligence Do for Me? (Part 2)
In my previous blog post, I described some concrete techniques and surveyed some early approaches to artificial intelligence (AI) and found that they still offer attractive opportunities for improving the user experience. In this post, we’ll look at some more mathematical and algorithmic approaches to creating usable business intelligence from big piles of data. Regression Analysis Regression […]
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 […]
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. […]
Self-Serve Advanced Analytics Requires Culture Change
Small and medium-sized businesses (SMBs) are often challenged to satisfy all the roles and responsibilities in the organization, and most team members wear more than one hat. That feeling of being overstretched is typical of growing businesses and, in an increasingly competitive market with businesses fighting for skilled resources, it is difficult to meet budget […]
Why Automated Data Extraction Matters in the Digital Age
In today’s fast-paced business world, one of the best ways for a modern enterprise to optimize processes is to rethink how to manage data. Business documents contain vital information for companies, irrespective of their size and industry. As most of these business documents contain unstructured data, automated data extraction has become a go-to option for […]
Solving Three Data Problems with Data Observability
Data collection, while crucial to the overall functionality and health of a business, does not automatically lead to success. If data processes are not at peak performance and efficiency, businesses are just collecting massive stores of data for no reason. Data without insight is useless, and the energy spent collecting it, is wasted. Effective use […]
Do You Need a Semantic Layer?
I co-founded my company to focus on the challenges of supporting a large number of data analysts working on disparate sets of data managed in a massive lake. We borrowed the term “semantic layer” from the folks at Business Objects, who originally coined it in the 1990s. The term was actually over 20 years old […]