The answer to this question is straightforward within the context of quantitative disciplines like mathematics in which “linear” and “non-linear” are well defined and differentiated. The answer is less obvious in reference to data management and analysis. The industry acknowledges that a traditional, strictly linear IT-centric approach is ineffective in view of today’s evolving data landscape.
When it comes to gathering the right data and finding the relationships that make that data more meaningful, there’s one role that knows how to do it best - the data steward. That’s why they are often referred to as data detectives.
Your organization’s data is a competitive advantage. But how can you take advantage of it, if you don’t know what you have? How can you leverage it to provide data-driven insights to decision makers? There are several roles in the organization who can help, starting with IT.
The Chief Data Officer has never been a more necessary role in the organization than it is today. Organizations capture and store more data than ever before, and it’s growing exponentially every year.
Not only is business data growing, but we are seeing new types of data continually entering the mix. Data is structured, unstructured and semi-structured. It’s stored in big data lakes, in business applications, in file shares, and other places across the organization. There’s so much data that even the CDO isn’t completely aware of what’s out there.
There's a lot of talk these days about how to streamline the data supply chain. And the discussions often boil down to how to control an organization's data and how difficult and time consuming it is for business users to access it. As I wrote recently for DataInformed, highly structured systems for managing data like master data management (MDM) and enterprise data warehouses (EDWs) put a kink in the data supply chain.
A splash of data used to be all you needed to get attention. Today, data-smart audiences want much more: detail, what-if scenarios, and deep, multi-sourced data for any questions they may have. They also want to see your work, from initial questions to final insights.
Smart organizations know the data they collect provides a wealth of insights that can help them meet the needs of their customers and drive competitive differentiation. But data today is a beast, coming from ever increasing sources and in a wide variety of formats.
As the Big Data and analytics parade marches on, I often find that the people we're talking to in large enterprises carry the title chief data officer or CDO. Industry analysts back this up. A 2015 report by PwC found there were 100 CDOs in large enterprises in 2013, more than double the number in 2012. Gartner's most recent tally pegs the number at 950.
Business analysts and line-of-business (LOB) data users have plenty of robust, self-service BI tools at their disposal. What they often lack is a way to get all the most relevant data into those tools. In a TDWI Checklist Report, Dave Stodder, Director of TDWI Research for Business Intelligence, lists seven best practices for executing a successful data science strategy. Number five: Give Data Science Teams Access to All the Data.