For nearly five years, Anupam Trivedi, Senior Director of Credit Control Services at HSBC, has been on a journey to modernize the bank's decision ecosystem for retail credit lending. Supporting lending decisions for the largest bank in Europe is no simple feat. Overall, the HSBC system processes lending decisions for
My recommendations for action for all those who want to sharpen their target picture now Digitisation in the insurance industry continues to advance. Although every insurance company is moving at its own pace, there is a lot happening in the specialist areas: In marketing, projects around the customer journey are
On 14 January, we held a SAS chat on the business value and importance of modern analytics platforms. Participants from SAS and partners, including Intel, joined us from across the globe. We checked in from London, Oxfordshire, Johannesburg and Istanbul, as well as Knoxville, Atlanta, Cary and Florida in the
From national parks and healthcare to taxes and nutrition, federal civilian agencies feature an incredibly large and diverse set of missions. These agencies oversee almost every aspect of American life with an endless sea of projects, programs and general oversight. But, as Deloitte Consulting’s Mark Urbanczyk said during a recent
Helmut Plinke explains why modernizing your data management is essential to supporting your analytics platform.
A number of posts on SAS Voices have touched upon the theme of modernization. This is certainly a hot topic with our customers as many of them continue to be interested in taking advantage of the evolving software landscape. The thing is, modernization can be hard. I should know, I’ve been
Much of my recent work has been along the theme of modernization. Analytics is not new for many of our customers, but standing still in this market is akin to falling behind. In order to continue to innovative and remain competitive, organizations need to be prepared to embrace new technologies
Unless you live in England, you may not have seen the recent announcement that Buckingham Palace is to undergo a 10-year refurbishment costing the British taxpayer £369M. Even with the post-Brexit devaluation of Sterling, that’s still a sizable spend representing nearly US$500 million. The Queen will remain in residence during
Yesterday I opened up the Wall Street Journal and found the usual mix of ads from major technology vendors touting their IoT (Internet of Things) prowess, and claiming they all have the secret sauce to make all of our IoT dreams come true. Where do I sign up?! Meanwhile, back
Some organizations I visit don’t seem to have changed their analytics technology environment much since the early days of IT. I often encounter companies with 70s-era base statistical packages running on mainframes or large servers, data warehouses (originated in the 80s), and lots of reporting applications. These tools usually continue
Two years ago, I found myself the proud, first-time owner of a garage. My wife and I quickly started to add new items to the garage – a battery-powered lawn mower, two beach cruisers and four Tommy Bahama beach chairs. They were stored with ease. What a fantastic world I'd been missing out on. But it wasn't long before we outstripped our
What does it really mean when we talk about the concept of a data asset? For the purposes of this discussion, let's say that a data asset is a manifestation of information that can be monetized. In my last post we explored how bringing many data artifacts together in a
.@philsimon channels his inner Queen Latifa.
A long time ago, I worked for a company that had positioned itself as basically a third-party “data trust” to perform collaborative analytics. The business proposition was to engage different types of organizations whose customer bases overlapped, ingest their data sets, and perform a number of analyses using the accumulated
Why they will still play a valuable role in organizational data-management and -integration efforts.
In my last post, I talked about how to observe the impact of modernisation through a data quality lens. I asked you to consider the quality of your legacy data and what that means on the "shiny new toy" you intend to buy in the future. In this post, I
.@philsimon with some recommendations on modernization.
Modernization is a term used to describe the necessary evolution of information technologies that organizations rely on to remain competitive in today’s constantly changing business world. New technologies – many designed to better leverage big data – challenge existing data infrastructures and business models. This forces enterprises to modernize their approach to data
In my last post, I started to look at the use of Hadoop in general and the data lake concept in particular as part of a plan for modernizing the data environment. There are surely benefits to the data lake, especially when it's deployed using a low-cost, scalable hardware platform.
Modernization is a term used to describe the necessary evolution of information technologies that organizations rely on to remain competitive in today’s constantly changing business world. New technologies – many designed to better leverage big data – challenge existing data infrastructures and business models. This forces enterprises to modernize their approach to data
Absent a strong executive presence, most mature organizations will continue to muddle through data integration.
At some point, your business or IT leaders will decide – enough is enough; we can't live with the performance, functionality or cost of the current application landscape. Perhaps your financial services employer wants to offer mobile services, but building modern apps via the old mainframe architecture is impractical and a replacement
More and more organizations are considering the use of maturing scalable computing environments like Hadoop as part of their enterprise data management, processing and analytics infrastructure. But there's a significant difference between the evaluation phase of technology adoption and its subsequent production phase. This seems apparent in terms of how organizations are
What's more, CXOs who believe that they can substitute data scientists for real data integration are as foolish as the duffer who consistently uses the wrong club.
If you were to climb Mt. Everest, you would face many dangers, including large crevasses in the glacier. Without best practices and a phased ascension there is a large probability that you’ll get into serious trouble and fail. When it comes to updating your data and analytics systems, the challenges
Imagine your company's analytics environment is like an old apartment building, with each unit having its own air conditioner. Each air conditioning unit has to be individually maintained and repaired by the building landlord or "super." The air conditioning units come from different manufactures and are of varying ages. It can be challenging, to
Do you “buy and build as you go” with your analytics architecture? Most companies do, and have for decades. The result is a heterogeneous environment for analytics with a variety of hardware, software, databases and analytical applications used in silos. There’s tremendous duplication of data and inconsistency in the analytical
Demand for analytics is at an all-time high. Monster.com has rated SAS as the number one skill to have to increase your salary and Harvard Business Review continues to highlight why the data scientist is the sexiest job of the 21st century. It is clear that if you want to be
