Big data presents an exciting opportunity for many organizations. To take advantage of that opportunity, one must understand the available technology options. This session defines the Enterprise Management Associates’ (EMA) Hybrid Data Ecosystem (HDE), discusses current technical solutions, and shares in-depth market research on how solutions enable the adoption of big data use cases, such as the Internet of Things. Failure to manage your HDE vendor and product portfolio will waste time, capital, and staff resources; discourage project sponsors and data consumers; and fail to achieve the full potential of your big data environment.
Understanding the strategic and functional differences between the components of the HDE and the impact of various implementation avenues (on-premises, cloud, managed service) is critical to developing a successful HDE strategy. Instead of knee-jerk investing in a platform or homegrown solution that will require eventual replacement, organizations should invest in platforms and vendors with the flexibility and adaptability to meet future business requirements. This course includes a discussion of standard approaches and how to effectively evaluate various platforms within the EMA HDE.
Solutions have a wide range of costs, and the differences between “low end” and “high end” products are often hidden in the features or in how the product works. This course presents effective product evaluation processes that empower your organization to recognize the critical details of your HDE environment and what you need to achieve.
Session participants will learn the following.
- The composition of the EMA Hybrid Data Ecosystem and its platforms
- The impact of on-premises, cloud (private, hybrid, public), and managed services implementation avenues as well as an overview of the marketplace and vendors’ product positioning
- Top technological vendor evaluation selection criteria to improve the probability of developing a successful HDE
- Common challenges to the implementation of HDE platforms
- Business managers and end users; BI directors; business analysts; BI application owners; data management staff; program and project managers; all non-IT business audiences