Data management and integration demands continue to increase as organizations are faced with more data flowing in from a greater variety sources than ever before. At the same time, there is the need to extract business value, protect, and offer wider access to that data for more users. Today, being data-driven is the goal of all companies, whether long established or born digital.
“Don’t bring a knife to a gunfight,” is how Michael Corey, co-founder of LicenseFortress, advises companies that are going to get audited by their software vendors. Conducting license compliance checks for over ten years, Corey has witnessed several instances where companies fail to understand software licensing nuances and lack knowledge around license metrics pertaining to software deployment, usage, configurations, and cloud architectures. Such blind spots are why software vendors like Oracle, IBM, and Microsoft find software audits an easy way to generate additional revenue.
Today, there is a constantly evolving list of data management issues that organizations are contending with. In addition to pressures of exploding data volumes, there is urgent demand for real-time, data-driven insights as well as more widespread data access. Expanding regulatory mandates also demand greater data quality and governance, as do cybersecurity threats.
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The assortment of challenges and resulting solutions is wide-ranging. With data flowing into organizations from more sources than ever, the requirement for efficient data integration and data cleansing has never been greater. In addition, due to the growing assortment of data privacy regulations, the need for data governance best practices has also increased. At the same time, a variety of cloud scenarios are on the rise, data warehouse approaches are working alongside data lakes, and numerous data management technologies are being tapped to address specific requirements.
Snipit: Startups with a mission to address an unanswered problem continue to emerge in the tech sector. These companies tap into new and still emerging technologies such as cloud, IoT, machine learning, containerization, AI, NoSQL, and blockchain to provide fresh solutions that simply were not possible before.