When planning for a day of business, how do you calculate the numerous factors that may affect your bottom-line revenue? For Serco, a company which operates a bike-sharing service throughout London, the answer was in their data.
Turning raw data into improved business performance is a multilayered problem, but it doesn’t have to be complicated. To make things simpler, let’s start at the end and work backwards. Ultimately, the goal is to make better decisions during the execution of a business process. This can be as simple
We live in the age of connectivity. Everyone and everything is constantly connected; yet, in most organizations, business unit planning operates in silos. This fragmented approach is often the result of spreadsheet-driven planning processes, which impede collaboration.
As we enter a new era of
IBM Watson Knowledge Catalog (WKC) provides a modern machine learning (ML) catalog for data discovery, data cataloging, data quality, and data governance. Within this framework lies a central Knowledge Catalog that serves as a single source of truth for data engineers, data stewards, data
A survey of end-users of Data Integration and Integrity (DII) software conducted by IDC in 2019 found that dynamic data movement, also known as data replication, is best served by stand-alone or platform tools, not custom code. When it comes to replication of data that is located in Virtual Storage
As companies progress on their Journey to AI, there is considerable focus on what needs to be available to build AI driven applications. The rungs of the AI ladder, which are best described as Collect, Organize, Analyze, Infuse, and Modernize are designed to strengthen a company’s use of AI.
Today, we are pleased to announce the general availability of IBM Cloud Pak for Data V3.0. Over the past two years we have advanced our platform from a collection of mostly IBM data services to a robust end-to-end data & AI solution that serves, along with the other IBM Cloud Paks. With V3.0,
A colleague recently shared a great quote with me from a mainframe CTO expounding on which platform is the “blue ribbon” winner for managing data across mainframe, IBM i, UNIX and Windows.
“While everyone scurried around to figure out what platform won,
a clear victor emerged: data”
As the world confronts new challenges, it is a unique, unprecedented time to recast old ways of working and redefine industries. At this moment, although it may seem that global business is at its quietist, beneath a veneer of calm, feverish transformations are taking place across markets, behind
IBM SPSS Statistics provides a powerful suite of data analytics tools which allows you to quickly dig into your data with a simple point and click interface and enables you to extract critical insights with ease. Organizations of all kinds have relied on IBM SPSS Statistics for decades to help
Africa is no stranger to the challenges of infectious diseases. Since 2015, hawse have addressed the likes of Bubonic Plague, Dengue Fever, Ebola, Measles, Middle East Respiratory Syndrome (MERS), Yellow Fever, and Zika Virus—at the cost of hundreds of thousands of lives across the continent. As
Keeping up with modern business
Business analysts today are expected to deliver insights and decisions on demand. Yet with continually increasing data complexity and volume, business analysts find it more and more challenging to produce accurate results in a timely fashion.
A common business hurdle
In today’s digital world, there is a guiding principle when it comes to enterprise information management – data privacy. Every regulation builds around it and CIOs consider it a common-sense business practice that is built into the fiber of their IT systems. Let’s think about the daunting