Optimizing Your Data Analytics Resourcing

A Data Strategy is a plan for moving an organization towards a more data-driven culture. A Data Strategy is often viewed as a technical exercise. A modern and comprehensive Data Strategy addresses more than just the data; it is a roadmap that defines people, process, and technology. The people aspect includes governance, the execution and enforcement of authority, and formalization of accountability over the management of the data.

From AI and machine learning to data discovery and real-time analytics, a strong data architecture strategy is critical to supporting your organization's data-driven goals. Greater speed, flexibility, and scalability are common wish-list items, alongside smarter data governance and security capabilities. Many new technologies and approaches have come to the forefront of data architecture discussions, including data lakes, in-memory databases and engines like Spark and cloud services of all shapes and sizes.

Rapidly evolving business needs drive unprecedented demand for the benefits of master data management (MDM) across a wider array of data, processes and operating entities. They also drive more questions from data and analytics leaders about what they must do to meet those needs and take full advantage of master data management. Join this complimentary data and analytics webinar as Gartner expert Thornton Craig fields your and your peers’ most-pressing questions about MDM, including about the essentials of MDM, implementation red flags and the importance of data governance.

Data scientists’ time is valuable. Computing resources are expensive. With only 87% of projects ever making it to production (Source: VentureBeat), organizations often overcommit to costly projects that bear little fruit. Data science teams need a way to assess project feasibility without diving head first.