Metadata powers effective action on information by providing context, content, and structure. When this information is managed well, data consumers can find and get the correct data they need. As Atlan Prukalpa Sankar states, “Metadata is the glue that can bind the modern data stack together, the layer that will allow increasingly diverse, siloed tools and people to collaborate effectively.” Grasping the […]
How Generative AI Will Transform Business
Generative AI – specifically ChatGPT – has taken the world by storm. From writing about AI in a Shakespearean style to basic programming, ChatGPT promises to disrupt existing workflows and reengineer daily life. In the meantime, companies face another revolution with generative AI. They can remove all the data fed to ChatGPT, then replace it with a company’s […]
Blockchain Technology Demystified
Prepare for blockchain technology to play a significant role in business, society, and almost everything. While 45% of CIOs said their organizations had yet to invest in blockchain between 2016 to 2021, that will change as information exchange becomes decentralized and demonstrated use cases show blockchain’s success. Blockchain spans various industries, from real estate, insurance, health care, […]
Data Literacy Training for Data Engineers
It may seem counterintuitive to think of data engineers needing to improve Data Literacy, the ability to read, work with, analyze, and argue with data. After all, data engineers apply technical Data Literacy skills to build and optimize operating systems and pipeline channels. At the same time, data engineers show gaps in using organizational Data Literacy and communicating […]
Metadata Management vs. Master Data Management
Businesses rely on knowing their data to survive and grow. Metadata management and master data management (MDM) provide essential processes for organizations to gain this knowledge and succeed. As a result, both need to be managed well. However, the differences and intersections between metadata management vs. master data management are often complicated to disentangle for […]
What Is Data Quality?
The Data Management Body of Knowledge (DMBoK) defines Data Quality (DQ) as “the planning, implementation, and control of activities that apply quality management techniques to data, in order to assure it is fit for consumption and meet the needs of data consumers.” Since expectations about DQ are not always verbalized and known, an ongoing discussion […]
Data Lineage Demystified
Trusting big data requires understanding its data lineage. Without data lineage, big data becomes synonymous with the last phrase in a game of telephone. The original data from the first person (e.g., “a guppy swims in a shark tank”) changes to something completely different when it ends with the last person (e.g., “The puppy that […]
Data Literacy Trends in 2023: Formalizing Programs
Data Literacy, the ability to explore, understand, and communicate with data, will significantly increase its role in organizations in 2023 and beyond. Companies will gravitate toward Data Literacy to get insights from big data and mobilize artificial intelligence (AI), a technology underlying a machine’s ability to learn from experience. Unfortunately, many businesses need to ramp up […]
What Is a Data Lake?
A data lake is an environment where a vast amount of data, of various types and structures, can be ingested, stored, assessed, and analyzed. Data lake technologies can scale to massive volumes of data, and combining datasets is easy with data stored in a relatively raw form. A data lake architecture can centralize data over distributed storage, providing a scalable, […]
Databases vs. Hadoop vs. Cloud Storage
How can an organization thrive in the 2020s, a changing and confusing time with significant Data Management demands and platform options such as data warehouses, Hadoop, and the cloud? Trying to save money by bandaging and using the same old Data Architecture ends up pushing data uphill, making it harder to use. Rethinking data usage, storage, and computation is […]