Descriptive analytics, or business intelligence, uses historical information to answer the question “What Happened?” Think of it as a rear-view mirror into business performance or a summary view of facts and figures in an understandable format to either inform or prepare data for further analysis. Observations, case studies, and surveys form the basis of descriptive analytics. Descriptive […]
Machine Learning vs. Deep Learning
The debate on machine learning vs. deep learning has gained considerable steam in the past few years. The fundamental strength of both these technologies lies in their ability to learn from available data. Though both of these offshoot AI technologies triumph in “learning algorithms,” the manner in which machine learning (ML) algorithms learn is very […]
What Is Data Mining?
Data Mining is an older (and now allied) subset of machine learning and artificial intelligence that deals with large data sets. It uses pattern recognition technologies with statistical and mathematical techniques to forecast business trends and find useful patterns. “Data mining is also known as Knowledge Discovery in Data (KDD).” A component of data mining, […]
The Future of Analytics: What is All the Hype About?
Expert’s ears immediately perk up upon attending a talk about how to get big insights from analytics. After all, analytics has become the new hot topic of the day. However, asked Nipa Basu, during her keynote presentation The Future of Analytics at the DATAVERSITY Enterprise Analytics Online Conference: “What is the difference between hype and […]
A Brief History of Data Quality
The term “Data Quality” focuses primarily on the level of accuracy possessed by the data, but also includes other qualities such as accessibility and usefulness. Some data isn’t accurate at all, which, in turn, promotes bad decision-making. Some organizations promote fact checking and Data Governance, and, as a consequence, make decisions that give them an […]
Case Study: PrecisionProfile Advances Healthcare Analytics with Improved Data Preparation
There’s one phrase that people never want to hear from their doctor: “I’m sorry, but you have cancer.” According to the National Cancer Institute, an estimated 1,735,350 new cases of cancer will be diagnosed in the United States this year and 609,640 people will die from the disease. Fortunately, and despite these statistics, many types […]
The Logical Data Fabric: A Single Place for Data Integration
The ability to provide a single place for instantaneous data access can mean business continuity or closure. Many nations found this out during the recent global crisis, as countries needed to know the number of tests taken and the infection rate in order to determine both the virus’ spread and who to quarantine. Unfortunately, the […]
Data Strategy and Machine Learning: How Do They Intersect?
With the tremendous growth of business data in terms of volume, size, and complexity, it is imperative that global enterprises develop a strong Data Strategy to address their core business needs. However, a realistic Data Strategy has to incorporate a clear road map with milestones, so that strategy documents do not end up as digital […]
How is Bad Data Crippling Your Data Analytics?
Some striking evidence of the impact of bad data can be found in fake email IDs, impersonations on social media, or misuse of stolen financial or personal information. The more widespread harm can be caused by bad data in Data Analytics, where anything from the wrong medical diagnosis to incorrect interpretation of stock history can […]
What Is Data Science?
Data Science is a combination of scientific disciplines “to build predictive models that explore data content patterns,” according to the Data Management Body of Knowledge (DMBoK). Data Science, formerly known as applied statistics: “Integrates methods from mathematical, statistical, computer science, signal processing, probability modelling, pattern recognition machine learning, uncertainty modeling and data visualization towards gaining […]