Data Science Articles

Cheat Sheet / Updated 04-27-2022

A predictive analytics project combines execution of details with big-picture thinking. These handy tips and checklists will help keep your project on the rails and out of the woods.

Cheat Sheet / Updated 04-25-2022

Data science affects many different technologies in a profound manner. Our society runs on data today, so you can’t do many things that aren’t affected by it in some way. Even the timing of stoplights depends on data collected by the highway department. Your food shopping experience depends on data collected from Point of Sale (POS) terminals, surveys, farming data, and sources you can’t even begin to imagine. No matter how you use data, this cheat sheet will help you use it more effectively.

Cheat Sheet / Updated 04-15-2022

A revolutionary change is taking place in society and it involves data science. Everybody from small local companies to global enterprises is starting to realize the potential of data science and is seeing the value in digitizing their data assets and becoming data driven. Regardless of industry, companies have embarked on a similar journey to explore how to drive new business value by utilizing analytics, machine learning (ML), and artificial intelligence (AI) techniques and introducing data science as a new discipline. However, although utilizing these new technologies will help companies simplify their operations and drive down costs, nothing is simple about getting the strategic approach right for your data science investment. This cheat sheet gives you a peak at the fundamental concepts you need to be on top of when building your data science strategy. It looks not only at investing in a top performing data science team, but also what to consider in your data architecture and how to approach the commercial aspects of data science.

Cheat Sheet / Updated 04-12-2022

Big data makes big headlines, but it’s much more than just a buzz phrase or the latest business fad. The phenomenon is very real and it’s producing concrete benefits in so many different areas – particularly in business. Here you will get to the heart of big data as a business owner or manager: You will take a look at the key terminology you need to understand the crucial big data skills for businesses, ten steps to using big data to make better decisions, and tips for communicating insights from data to your colleagues.

Cheat Sheet / Updated 03-25-2022

Whether you’re a small business owner or work for a global corporation, you deal with information every day. You receive information, you send it, you determine what’s relevant, and you make decisions, whether consciously or subconsciously, about what information to retain. That’s why records management — managing the flood of information you get every day — should be such an important part of your business strategy. This Cheat Sheet can serve as a quick reference to some of the main aspects of record management.

Cheat Sheet / Updated 03-10-2022

Summary statistical measures represent the key properties of a sample or population as a single numerical value. This has the advantage of providing important information in a very compact form. It also simplifies comparing multiple samples or populations. Summary statistical measures can be divided into three types: measures of central tendency, measures of central dispersion, and measures of association.

Cheat Sheet / Updated 03-01-2022

SAS Institute has hundreds of statistical analysis system products, so a partial list of the ones you might run will help you know which one to use for your job. The tasks in SAS Enterprise Guide and SAS Add-In for Microsoft Office create SAS programs that call on SAS procedures. Having a list of those procedures and being able to find them quickly in SAS Enterprise Guide will boost your efficiency.

Cheat Sheet / Updated 03-01-2022

Microsoft Power BI is an enterprise-class data analytics and business intelligence platform that users connect to for data analysis, visualization, collaboration, and distribution. The platform takes a unified, scalable approach to business intelligence that enables users to gain deeper data insights while using virtually any data source available. With Power BI, you can access tools to support the entire data analysis lifecycle — from importing to transformation to visualization and collaboration. Power BI, as part of the Microsoft Power Platform, is complementary to its sister application of Power Apps (for no-code/low-code application development), Power Automate (for workflow development), and Power Virtual Agents (for chatbots.). Each of these applications works well with one another. Strong integration opportunities also exist between Microsoft 365 (Word, Excel, PowerPoint, and SharePoint) and Dynamics 365. When you’re looking to realize the value of your data using Microsoft applications, or even third-party applications, Power BI can provide the insights you and your organization look for at speed and scale.

Cheat Sheet / Updated 02-28-2022

Algorithms are fun! Algorithms are beautiful! Algorithms are even better than your favorite pastime! Well, perhaps not the last one. In fact, algorithms surround you in many ways you might not have thought about, and you use them every day to perform important tasks. However, you need to be able to use algorithms in a way that doesn’t involve becoming a mathematician. Programming languages make it possible to describe the steps used to create an algorithm, and some languages are better than others at performing this task so that people can understand it without becoming a computer or data scientists. Python makes using algorithms easier because it comes with a lot of built-in and extended support (through the use of packages, datasets, and other resources). With that in mind, this Cheat Sheet helps you access the most commonly needed tips for making your use of algorithms fast and easy.

Cheat Sheet / Updated 02-25-2022

A data lake is an enterprise-scale home for analytical data from all corners of your company or governmental agency. No matter what your analytical data landscape looks like today, your organization will benefit from building a data lake.