Companies were engaged in Data Governance practices such as Data Lineage and Data Quality for years before the concept of Data Governance emerged as a mainstream enterprise-level activity in 2005, said Kelle O’Neal, the founder and CEO of First San Francisco Partners, during her DATAVERSITY® Enterprise Data Governance Online event presentation titled Data Governance 2.0. […]
Addressing Edge Computing Needs with Advanced Data Storage
The number of companies using edge computing is rapidly growing as real-time insights are becoming more important to business success. Edge computing “uses a network of microdata servers to process and store Big Data locally, taking the concept of a distributed architecture to the next level.” It is meant to help decrease latency problems, allow […]
Modernize Data Practices with DataOps
Back in 2015, a new term was introduced to the market: DataOps. “DataOps,” wrote Andy Palmer: “Is a Data Management method that emphasizes communication, collaboration, integration, automation and measurement of cooperation between data engineers, data scientists and other data professionals.” The practice was born out of the democratization of analytics and the implementation of built-for-purpose […]
Data Virtualization for a Hybrid World
Many organizations see the hybrid cloud and multi-cloud models as critical to their present business requirements, and to their future ones too. Organizations are paying more attention to the use of containers to help with simple and automated portability and scaling that can play an important role in accelerating cloud projects and deliverables; to cloud […]
Harvest Data Lineage to Build Effective Data Governance
Being able to trace data from its origin to its destination is no longer a nice-to-have. It’s a must-have if you are to govern data — and of course you’ve got to govern data. Without metadata, data lineage can’t exist, and if data lineage can’t exist, neither can Data Governance. Metadata brings together assets and […]
Data Governance and Data Discovery: Enabling Data Regulation Implementation
Businesses are continuously striving to leverage data-driven insights or competitive intelligence, the concept of developing an organizational “data culture” will gain prominence. Data and data analytics will continue to play key roles in global businesses of the future. According to the article Why Data Culture Matters: “Organizational culture can accelerate the application of analytics, amplify […]
Bringing Hyperconvergence Architecture and VDIs to Everyone
A hyperconverged infrastructure (HCI) uses software and/or hardware to create an IT infrastructure that virtualizes all of the needed elements to create an efficient and highly functional computer processing system. An HCI includes compute, networking, and a storage combined together in a virtualized environment, and normally runs on easily purchased, off-the-shelf commercial servers. The primary […]
The Challenge of Scaling Transactional Databases
Generally speaking, databases are storage systems with various built-in software features to manage the movement of data within. A database management system (DBMS) describes software controlling other programs and applications. The creation and implementation of a well-designed database is a serious challenge. With the evolution of data volumes and constantly changing needs, new types of […]
Data Strategy and Serverless Computing: How Do They Work Together?
Businesses need a strong Data Strategy to manage vast amounts of data, drive innovation, develop a data culture, and to maintain a competitive advantage. Though cloud environments offer fast, high-volume data collection and scalable storage space; machine learning-powered data preparation; AI-enabled analytics; data backup and recovery facilities — leaving the developers free to pursue coding. […]
Data Modeling in an Agile World
Data Modeling creates a model for storing and processing data that works in a predictable, consistent manner. It includes the visual presentation of data structures, while enforcing business rules and government policies. A data model focuses on the needed data and its organization, rather than the operations performed on the data. Data Modeling is done […]