As organizations recognize the positive impact that big data has on a company’s performance and innovation, the position of Chief Data Officer (CDO) continues to grow in prominence across numerous industries.
The evolution of big data over recent years has resulted in a new role that has been gaining industry traction – the Chief Data Officer (CDO). As executives begin to recognize the business value residing in their data, they are focusing now more than ever on finding ways to manage and govern this data. The CDO is emerging as a key player in the enterprise by helping to establish and maintain data governance, quality, architecture and analytics, enabling firms to more productively harness information to manage risk, reduce cost and drive innovation.
On my flight back to Boston from Grapevine, TX, where we spent three exhausting and exhilarating days at Gartner BI & Analytics Summit, I am reflecting on the great interest shown in Cambridge Semantics Smart Data Lake at this event.
Data lakes are no longer anomalies. Consolidating all of an organization’s data—unstructured, semi-structured, and structured—into a single repository for integration, access, and analytics purposes is rapidly emerging as the preferred way to manage big data initiatives.
Many data lake projects achieve their IT objective: cheap storage of all enterprise data in raw form, but fail in their business objective to deliver value from this data. Why? Because making the data accessible and usable for business users is hard.
Ernst and Young just released their 2015 Federal Reserve regulatory reporting survey looking at how firms are adapting to the new standards. The survey covered 5 key topics but two stood out as areas where new smart data solutions could add immediate value for the banks: Report Preparation and Data &Technology.
In a recent buyer case study, IDC examines the use of the Anzo Smart Data Platform by PricewaterhouseCoopers (PWC) in a sophisticated new class of financial Risk and Compliance solutions.
The Data Lake promises to transform enterprise data management and analytics by providing ubiquitous access to all enterprise data. Unlike traditional data warehouses that are often inflexible, brittle and expensive, the data lake accommodates any type of data and stores it cheaply, in very large volumes, on commodity hardware.
A round up of recent industry news on the topics of Big Data and Enterprise Data Management
Driving business value from your data often requires integration across many sources. These integration projects can be time consuming, expensive and difficult to manage. Any short cuts can compromise on quality and reuse. In many industries, non-compliance with data governance rules can put you firm’s reputation at risk and expose you to large fines.