7 Steps to Mastering Data Preparation for Machine Learning with Python Author: Matthew Mayo, KDNuggets Source: https://www.kdnuggets.com/2019/06/7-steps-mastering-data-preparation-python.html How: Pandas library, Python, EDA (Exploratory Data Analysis) When to use this: when…

The volumes and sources of data are snowballing. To support this avalanche of data are a growing number of applications and tools for analytics and data science. (more…)

When departments can't get the data analytics support they need, it can hinder progress for your company and risk your competitive edge. This lack of support can arise when people…

Not being able to tell where to prioritize your investment decisions is not anyone's idea of a good business plan. Whether you're a CEO or a small business owner, you…

As a data specialist, expectations are high. Data scientists are perceived as essentially magicians, who can wrangle data, whip up an algorithm and pull a result out of their hat.…

Many IT or operations managers are expected to provide data and analytics to help their organizations achieve and keep a competitive edge. Yet not all in these roles have the…

Do you struggle to find qualified candidates for data analytics positions? Are job descriptions and hiring requirements sometimes vague and other times overly technical? (more…)

Introducing Chisel Analytics Each year, companies produce volumes of data from operations, transactions, web activity, and IOT, creating an avalanche of information available to those looking to better serve customers…

In short, analyzing data is important because it assists businesses in making decisions. Data is just facts, figures and information waiting to be organized. Analyzing data is the process of…

Take Assessment As the volume and sources of data has grown, so have the possible applications of analytics and data science. And with the advent of techniques such as machine…