Data Quotes The amount of data generated in real time is immense. This has created oceans of data from which companies can derive real business value and make better business decisions. The big data market is predicted to grow by 20% this year, and by 2020, every human is expected to generate 1.7 megabytes (of […]
Data may be the buzzword of the decade (and the oil of the 21st century), but without the right storytelling tools, data is just data—boring, confusing, and uninspiring. Thankfully, it’s easier than ever before to find the data visualization tools you need to start transforming numbers and statistics into workable strategies and business goals—and on a […]
In my last post, we explored a general overview of data analysis methods, ranging from basic statistics to machine learning (ML) and advanced simulations. It was a pretty high-level overview, and aside from the statistics, we didn’t dive into much detail. In this post, we’ll take a deeper look at machine-learning-driven regression and classification, two […]
Data is constantly changing: from business addresses and names to contact phone numbers and email addresses. Data that was useful weeks or months ago quickly becomes outdated and new data needs to be incorporated into decision-making. The purpose of data analysis is to remove bias and use historical data to create actionable recommendations and predictions […]
Data is in and data is hot, because data is valuable. The big data revolution has demonstrated that the modern, interconnected world is brimming with data-based insights waiting to be revealed. That’s where data analysis methods come into play. Whether you’re self-employed, work at a small business, or partake in the corporate world, it’s likely […]
The demand for qualified data analysts is high and increasing. But employers aren’t just looking for people with the right technical skills; the ideal job candidate needs to excel at business thinking as well. That’s why we partnered with Microsoft to create the Data Analytics Career Track. We offer a unique approach to an analytics curriculum. […]
Data analysts take raw input and make magic happen. This “magic” process of making data more palatable (or more importantly, useful) is called the data pipeline. To get there, you need the right data analytics tools, but what are the right tools? We’ve curated a list of useful software—an extended data analytics stack—that data analysts […]
In this post, we’ll define quantitative data, share quantitative data examples, and outline the differences between qualitative and quantitative data (and other data types). But first, let’s take a step back. From test scores to satisfaction ratings to tweets, 2.5 quintillion bytes of data are generated every day. But not all data is created equal. […]
