In this era of big data, chances are that you have heard and used terms like machine learning and predictive modeling. For the average person, these terms may actually seem interchangeable. However, in the world of data analysis, there are big differences between these terms. In fact, these tools are used differently to provide different kinds of insights and add different strategic value. Today, we will take a closer look at predictive modeling, machine learning, and artificial intelligence, and discuss when to use them for the best results.
Once upon a time, spreadsheets were a holy grail and a force to be reckoned with. Spreadsheets revolutionized how business was done by offering a way to collect and organize data. Companies relied on them for almost everything in the business ranging from accounting to sales and even operations. They used the software to analyze data while generating reports.
However, spreadsheets are slowly becoming outdated. They can no longer keep up with the needs of our tech-forward world and changing business requirements. This article offers reasons businesses must upgrade their primary source of data consumption from spreadsheets to better alternatives.
Nowadays, data is everywhere. It is a commodity of incalculable value. Almost everything you do results in the creation of new data. For example, when you withdraw money from a bank, data is created and stored. Similarly, when you visit a website, you create data that Google and other third-party companies can store and use.
As the era of big data kicks into high gear, businesses and organizations are now more focused on how they can leverage the data to gain a competitive advantage. This has, in turn, powered the popularity of data science tools - specifically the concepts of analytics and visualization. Despite hearing these words on every street corner in major cities, some business owners are still in the dark about what they actually are and how they can use them to grow their entities. If you're among them, don't worry, this definitive guide outlining the differences between data analytics and data visualization will help shed light on how to use them to improve your company.