This datagram quickly explains the nine levers that enable organizations to create value from an ever-growing volume of data from a variety of sources -- value that results from insights derived and actions taken at every level of the organization.
I’ve encountered many customers who are keen to ditch their data warehouse and use Hadoop to store the organization’s data as a cost-saving measure and to provide more flexibility to the business. However, an oft-overlooked consequence of eliminating the data warehouse is that analysts are now
This is Part 2 of our series on the findings and text from IBM Institute for Business Value’s latest study and paper - “Analytics: A blueprint for value - Converting big data and analytics insights into results”.
In Part 1, we introduced the concept of nine levers that represent the sets of
In late October 2013, the acclaimed IBM Institute for Business Value (IBV) released a new study titled “Analytics: A blueprint for value.” This study is the result of months of survey research conducted with some 900 business and IT leaders around the world. As the title “a blueprint for value”
Twice recently, in two different large companies, people whom I have otherwise respected as being quite sensible have said to me that their organisations had appointed people who, within their own function, were ‘responsible for data quality’.
Well, when I went to Data Governance School back at the
Data science can only function as a sustainable business resource if it’s managed professionally. Regardless of how your organization chooses to organize your data scientists, you need a layer of professional management. The core reasons for this are clear:
keep data science initiatives aligned
In today's competitive marketplace, executive leaders are racing to convert enterprise insights into meaningful results. Successful leaders are infusing analytics throughout their enterprises to drive smarter decisions, enable faster actions and optimize outcomes. In this exciting new piece of
My previous blog posts have been focused on how analytics can help drive telematics to the mass market and help identify who is suitable for a telematics policy. In this blog we take a step back to consider the data privacy and security issues around the data that is generated from devices or apps
Speed of thought is something we like to imagine operates at a single high-velocity setting. But that’s just not the case. Some modes of cognition are painfully slow, such as pondering the bewildering panoply of investment options available under your company’s retirement plan. But some other modes
In my last post, we explored how audience data sources from inside and outside of the media organization can be “unified and utilized” for game-changing applications such as demand forecasting for Opening Weekend Box Office (OWBO) using big data analytics.
Our results showed that IBM achieved high
You don’t need to wait for the stars to align in order to realize the full value from your investments in analytics initiatives of all sorts.
Instead, what you need to do—and it’s within your power here and now—is to align several key dimensions of your organization’s analytics and data strategies
Rachel Bland, senior product manager for IBM Business Analytics, describes one of the many sessions on Analytics at Information On Demand 2013. This session will focus on IBM's latest in-memory technologies and how we're making them easier to use. Key points of this session are:
In my first post I introduced the idea that most “big data” isn’t really big at all, and doesn’t conform to Gartner’s 3V’s. Instead, I've suggested that there’s benefit in focussing on “broad data”, or the use of many different sources of data to give us richer information. We put forward 4O’s of
Many of my waking hours are spent explaining to people that “big data” is not as opaque and mysterious a concept as they’ve been led to believe. To the extent that I can hold their attention for a detailed technical discussion, I can alleviate their concerns that it might all be smoke or mirrors or