Companies awash with data—the twenty-first century’s new natural resource—are eager to tap into the Internet of Things and analytics to gain valuable insight for well-informed decision making. Organizations seeking to improve decision-making for human resources, sales and marketing, supply chains
Demand for data scientists is growing. Strong analytical skills and the ability to tap into the expertise of the larger analytical community helps new and seasoned data scientists keep up with new trends and continue to hone their skill sets.
Many companies ask themselves how they can adapt to the current technological landscape. Workforce analytics alone are not enough. Developing and managing talent and workforce along with strong advocacy to champion transformation leads to successful outcomes.
The Internet and our social feeds are chock full of blogs, news and articles on the strides that the public sector is making with big data and analytics. This Public Sector News series skims the wires and pulls out the most interesting articles that give us fodder for thought and debate.
Watch this live chat with our second group of teams and participants from the #Hadoop4Good challenge to learn why they chose their projects, hear some of their challenges and delve deeper into the story behind their applications.
Thoughtful analytics ought to offer measurable insight into how—qualitatively and/or quantitatively—more data correlates with enhanced economic value. Call it the metalytics—analytics about analytics—of value creation and discovery. Data-driven organizations need to take metalytics metrics
IBM Analytics solutions enable healthcare organizations to connect disparate information into a single trusted view and deliver insights into data. The industry-leading accuracy and performance of IBM InfoSphere Master Data Management is at the heart of a big data & analytics strategy. Armed
In the data-driven age, the most effective businesses know that success depends on making decisions based on hard facts rather than gut instinct. But how can you be confident that you are taking the right action, if you don’t fully trust the accuracy of the figures on which your decisions are based?
Watch this live chat with the teams and participants from the #Hadoop4Good challenge to learn why they chose their projects, hear some of their challenges and delve deeper into the story behind their applications.
In part seven of this series, we looked at the second key stage within the analytics lifecycle (Analyze), which focuses on analyzing the data and identifying the insights most likely to create a positive business impact. In part eight we will examine recommendations and practical actions for the
This week’s IBM Big Data & Analytics hero, James Taylor, CEO of Decision Management Solutions, says that too many projects “start with the data [and] then hope that this will improve the business.” Taylor advocates for businesses to “begin with the decision in mind.”
Fluidity is the degree to which your cloud data analytics resource can be rapidly and cost-effectively repurposed and reconfigured to respond to and proactively drive change in a dynamic world. The fluidity of the logical data warehouse depends on core interfaces, infrastructure and tooling that