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 posts on data analysis methods and machine learning, I briefly mentioned data cleaning and its importance. Those two articles were not focused on data cleansing, so they were indeed brief mentions. However, the importance of using (relatively) clean data is paramount in machine learning and statistics. Do We Really Need to Clean […]
For any job in any industry, the interview process can induce major anxiety. That’s especially true for a data analyst interview, when your communication skills and overall fit will be judged by people whose jobs literally are to analyze. Yeesh. The best way to combat the pre-interview jitters is to prepare yourself. That’s why we’ve […]
So, you want to work with data, but you’re not sure which area of expertise is right for you? At Springboard, we’ve developed several courses that teach students the skills they need to get jobs in different data-focused roles. Let’s break them down. Data analysts sift through data and provide reports and visualizations to explain […]
There has never been a more exciting time to work with data. The data analytics industry is predicted to reach almost $78 billion by 2023, and by 2020, there will be an estimated 2.7 million jobs open for data analysts and data scientists. But what exactly is data analytics? And how does it differ from […]
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 […]
