The primary purpose of implementing a Data Architecture is to standardize the methods and protocols, as well as the systems for acquiring, storing, managing, and sharing data across the enterprise for improved decision-making. In modern businesses, most decisions are made in real time, and to facilitate an efficient and real-time friendly Data Management infrastructure, data […]
A Brief History of Data Management
Data Management is the organization of data, the steps used to achieve efficiency, and gather business intelligence from that data. Data Management, as a concept, began in the 1960s, with ADAPSO (the Association of Data Processing Service Organizations) forwarding Data Management advice, with an emphasis on professional training and quality assurance metrics. Data management has […]
Data Quality Dimensions
Data Quality dimensions are useful concepts for improving the quality of data assets. Although Data Quality dimensions have been promoted for many years, descriptions of how to actually use them have often been somewhat vague. Data that is considered to be of high quality is consistent and unambiguous. Poor Data Quality results in inconsistent and […]
Better Data Modeling with Lean Methodology
The process used today in systems development started with principles developed for assembly lines in the 1950s, when manufacturers wanted a more disciplined approach to producing goods and services.Products would come off an assembly line, they’d be inspected, defects would be found, and would be sent back to rework or start from scratch. This process […]
Data Governance Trends in 2022
Way back in the early 2000s, Data Governance wasn’t really much of a thing. There were a few really early pioneers that were doing Data Governance, and they were laying the groundwork, but governance was not a recognized capability. Companies who did see some value in Data Governance were primarily focused on the benefit to […]
A Brief History of Data Architecture: Shifting Paradigms
Data Architecture is a set of rules, policies, and models that determine what kind of data gets collected, and how it gets used, processed, and stored within a database system. Data integration, for example, is dependent on Data Architecture for instructions on the integration process. Without the shift from a programming paradigm to a Data […]
Database Management Trends in 2022
Historically, Database Management systems (DBMS) were simple software programs and associated hardware that allowed users to access data from different geographical locations. The system offers its users the ability to store data without concerns about structural changes, or the data’s physical location. Additionally, a Database Management system (DBMS) can set restrictions on the data being […]
Case Study: Jerry’s Foods Improves In-Store Data Infrastructure
The ability for people to be able to buy food and essential supplies, in-store IT and data infrastructure must be kept running. Jeff Miller, Director of IT at Jerry’s Foods, a national chain with fifty grocery, retail, hardware, and liquor stores, knows this reality very well. Miller explains that each Jerry’s Foods franchise includes many […]
Data Quality, Data Stewardship, Data Governance: Three Keys
Typically, Data Governance programs start with Data Quality, because that is where end users or stakeholders begin to interact with data, especially from the reporting and analytics perspective. “They get a report that doesn’t match another report and they can’t marry it to other data,” said Mary Anne Hopper, Data Management Consultant at SAS Institute. […]
Data Governance Tools Support Data Management
Data Governance, and the tools supporting it, reflect the growing importance of “automated services” when dealing with the laws and regulations that have been developed to protect privacy and societal norms. Data Governance has become a necessity for organizations using the internet. It is a collection of rules, policies, and standards designed to improve Data […]