How did companies like Facebook and Airbnb get so big so fast? What can we learn from them? Why is data so important for growth? Nancy Hensley, Director of Strategy & Growth for IBM Hybrid Cloud, has the answers in this episode of Making Data Simple.
Although there are many new and emerging classes of data integration, quality and governance software tools available in the market, many large organizations are coming to the conclusion that they're best served by a single unified enterprise data integration, quality and governance platform that
There’s a revolution taking place within information governance. This change is driven by the growing needs of business users, and the recognition that trusted, high-quality, easy-to-find data can be the differentiator that drives better business outcomes.
If information is paramount, it becomes our collective responsibility to nurture, develop, secure and protect information. One should nurture and develop information so that it is well formed, mature and timely; and secure and protect information so that it is valued and guarded, not shared or
It’s no secret that most successful businesses today depend on data—and that’s more true of technology companies and start-ups than any other segment. The ability to analyze information, derive insight quickly, and make confident, timely decisions can often help a software company break into a new
If you joined us or tuned in for IBM’s Fast Track Your Data broadcast from Munich last week, you heard us talk about the history of cars – a most appropriate location for the discussion. But it wasn’t until Henry Ford and the assembly line over twenty years later that the automobile was advanced
Dez Blanchfield talks with Data Scientist & author Lillian Pierson about our Fast Track Your Data 2017 event in Munich, sharing general thoughts on the key themes and topics, in particular how organizations can secure their competitive advantage with machine learning.
We’re living through the third great revolution in modern business. First came economies of scale, which we harnessed with the Industrial Revolution, the assembly line, and the creation of global markets. Second was network effects, seen most obviously in the rise of the Internet and the Web. Third
It’s easy to be blinded (and impressed) with the rapid innovation and evolution in the arena of big data. Today’s most technically sophisticated companies have the opportunity to exploit big data tools to address mind-numbingly cool use cases and produce very enticing results. However, so many
In the past, the relationship between the different models that might be used in defining a data warehouse was a very linear one. There may have been different model artifacts used as the team responsible for developing the data warehouse progressed through the usually waterfall-type set of
For today’s data scientists and data engineers, the data lake is a concept that is both intriguing and often misunderstood. While there are many good resources about data lakes on ibm.com and other websites, there is also a lot of hype and spin. As a result, it can be difficult to get a clear
Data is often the catalyst that drives business direction and growth. However, if data is cryptic and not understood, then how can such data contribute to such direction or growth? Just like in life, we learn from our past, as we gain direction and insight from previous events or activities to make
In many cases the data lake can be defined as a super set of repositories of data that includes the traditional data warehouse, complete with traditional relational technology. One significant example of the different components in this broader data lake, is in terms of different approaches to the