According to Pat Patterson, Community Champion at StreamSets, “data drift” is such a problem now that “only about one fifth of a data analyst’s time is actually spent analyzing the data.” The remainder is spent “wrangling it into shape and getting it from where it is to the actual analysis platform.” Speaking at the Enterprise […]
Citizen Data Scientists: Where Do They Belong?
The phenomenal growth of data technology in recent years has led to the rise of the citizen data scientists (CDS). Developments in augmented analytics and artificial intelligence (AI) automation have now made it possible for ordinary business employees to conduct advanced analytics or business intelligence (BI) which would have required expert knowledge even some years […]
Tales of A Common Vocabulary, Data Quality, and Machine Learning, Oh My!
Order in the court! Order in the court! The case being heard is a serious one. The defendant—the Chief Data Architect of VeraVisionFake Inc.—is accused of having ignored the need to establish a valid and sound common data vocabulary in her organization. She is up against The Common Vocabulary Value regulatory agency, whose mission is […]
ETL vs. Data Preparation
Extract, Transform, and Load (ETL) technologies, managed exclusively by IT, have until recently been the primary tool used to combine data from multiple sources and thus provide the ability to drive important business decision making for organizations. But, with the advent of self-service data preparation, business users and subject matter experts (SMEs) can find those […]
Fundamentals of Self-Service Business Intelligence
It’s clear that there is considerable recent market movement towards self-service business intelligence (SSBI) in the numerous vendor offerings available. There is also a growing concern among the Data Science community that ordinary business users may misunderstand or misinterpret the available data, leading to incorrect results. Experienced data scientists have a tremendous ability to analyze, […]
Fundamentals of Robotic Process Automation and Data Management
Data Management software is essential to providing organizations with critical insights about their customer’s behavior. Robotic process automation (RPA) is a process in which software programs perform repetitive Data Management tasks, such as data validation, email responses, normalization, and metadata organization. Put another way, RPA automates the mundane. It does this by observing and imitating […]
Case Study: Feeding America Takes on Project to Standardize Data and Improve Data Quality
Feeding America is a domestic-hunger relief charity with a nationwide network of close to 200 member food banks that work together to provide food to more than 46 million people through 60,000 food pantries and meal programs. It secures donations from national food and grocery manufacturers, retailers, shippers, packers, growers, government agencies and other organizations. […]
So You Want to be a Machine Learning Engineer?
Ideally, a machine learning engineer would have both the skills of a software engineer and the experience of a data scientist and data engineer. However, data scientists and software engineers usually come from very different backgrounds, and data scientists should not be expected to be great programmers, nor should software engineers be expected to provide […]
It’s Time to Build a Cohesive Data Strategy
George Yuhasz is helping businesses to innovate in another direction: building a rich Data Strategy by holistically and concurrently bringing together analytics, Data Governance, and Information Architecture. As U.S. Director, Business Intelligence and Data Services, he launched the Data Strategy at the global food services enterprise. It’s been a job of optimizing people and processes, […]
Demystifying Metadata Management
As advanced analytics becomes a prominent driver of revenue in the data-driven age, technologies are needed to help provide a context to data. Business leaders and the global Data Science community have realized that businesses need appropriate technology to comprehend the context of business data. In addition to Data Governance, the Data Management strategy that […]