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Discover how AI data analytics tools assist data engineers in seven key ways, including automating routine tasks and supercharging data prep and ETL processes.
Explore top AI machine learning strategies for analytics success. From predictive modeling to explainable AI, unlock key insights for your projects.
It’s a smart idea to thoughtfully consider whether to build or buy an analytics application. Use this handy decision tree.
If you’ve been paying attention, you probably already understand the business value and the benefits of building a data team at your company. But what functions should they actually perform? In large companies, each of these tasks may be performed…
Data-driven companies are those that maximize the potential benefits of their data. The data functions at these companies have efficient processes to turn data into action and actions back into data. Becoming data-driven, and learning to translate data into better…
What Is Data Science? What Is Data Analytics? What Is the Difference? Big data has become a major component in the tech world today thanks to the actionable insights and results businesses can glean. However, the creation of such large…
Making the most of your business intelligence is equivalent parts having the right data and choosing the appropriate visualization to maximize it. The amount of data produced today means that simply reading through line after line of numbers becomes unfeasible…
SQL is the dominant language for data analysis because most of the time, the data you’re analyzing is stored in a database. And most analysis involves a lot of filtering, grouping, and counting — actions that SQL makes very easy….
Step 1: Strategy Step 2: Identify key areas Step 3: Data targeting Step 4: Collecting and analyzing Step 5: Action Items Want to improve your decision-making process? These days, gut instinct is no longer enough if you want to remain…
In the real world, latitude and longitude play an important role in several fields and calculations, but one of their most common uses is measuring distances between points. As a data company, we want to see our customers use this…
Realizing that you can only improve what you measure is a good way to think about KPIs. Often companies want to improve different aspects of their business all at once, but can’t put a finger on what will measure their…
Data preparation is perhaps the most important step in any type of serious data analysis. And while it would be ludicrous to attempt to cover such a broad field of knowledge in one article, we’ve prepared a quick checklist that…
When summarizing statistics across multiple categories, analysts often have to decide between using weighted and unweighted averages. An unweighted average is essentially your familiar method of taking the mean. Let’s say 0% of users logged into my site on Day…
Quantitative vs. Qualitative Measuring Quantitative Measuring Qualitative Implementing a Business Intelligence suite in your organization is about more than simply collecting additional data — it’s about converting this data into actionable insights. The amount of data an organization can collect…
With new possibilities for enterprises to easily access and analyze their data to improve performance, data modeling is morphing too. More than arbitrarily organizing data structures and relationships, data modeling must connect with end-user requirements and questions, as well as…