Data, Analysis, Automation and Integration
Data and analytics have become integral to the success of many companies and are the core of many organizations strategic plan. In recent years, the requirements for an enterprise solution has seen improvement. ZE, developers of the ZEMA Suite of products a leading enterprise data management company will share insight garnered from experience guiding clients in developing their own robust enterprise architecture. ZE has worked with companies of many types and sizes, including Fortune 100 companies, utilities, gas and oil companies, industrials, banks and exchanges to develop a robust enterprise platform to facilitate the flow of data, and analysis through their organization. This session will discuss the elements and best practice required for corporations to develop a robust homogeneous data and analysis ecosystem.
We will break down the discussion into the critical data components, data, analysis and integration and explore latest insights and trends. We will discuss the importance of data collection processes, market analysis, the value of automation of business processes and integration with downstream systems. We will also share our insights and benefits of best practice technology, architecture and internally hosted solutions compared to cloud and vendor hosted options.
We will explore:
- Managing multiple sources of data of varying types and timeliness
- Flexible analytic tools to meet varied needs of organization
- Business process automation
- Considerations of integration
Manal El-Ramly is Director, Global Markets for ZE. She joined ZE in it’s inception in 1995 and was responsible for the early development, adoption, and expansion of ZEMA on a global scale. Overseeing business development, sales and marketing team out of the Raleigh, North Carolina office, she leads field operations for commodity and financial companies. Manal’s mission is to ensure she continues to provide optimal advice and customer service to all of ZE’s clients.
Aiman El-Ramly, Information Resource Management in the Age of Big Data