mybigdata

In our data-rich age, understanding how to analyze and extract true meaning from the digital insights available to our business is one of the primary drivers of success. Despite the colossal volume of data we create every day, a mere 0.5% is actually analyzed and used for data discovery, improvement, and intelligence. While that may not seem like much, considering the amount of digital information we have at our fingertips, half a percent still accounts for a huge amount of data. With so much big data and so little time, knowing how to collect, curate, organize, and make sense of all of this potentially business-boosting information can be a minefield – but online data analysis is the solution. To help you understand the potential of analysis, the meaning, and how you can use it to enhance your business practices, we will answer a host of important analytical questions. Not only will we explore data analysis methods and techniques, but we’ll also look at different types of data analys

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and online data visualization. Companies need data scientists to help them empower their analytics processes, build a numbers-based strategy that will boost their bottom line, and ensure that enormous amounts of data are translated into actionable insights - enter the world of data science tools. But being an inquisitive Sherlock Holmes of data is no easy task. There are a number of tools available on the market, and knowing which one to choose to increase performance can be time-consuming, and often confusing. Not to forget various areas of data scientists employed in, from academia to IT companies. But we will not focus on their choice of industry, instead, we will take a closer look at the bas