If you have huge volumes of data, chances are that you can get value out of analyzing that data. But, would you derive significant value from analyzing it in real time? This is an important question because, while there are benefits to real time analytics, there are also real costs. To help you decide whether […]
There exists a chronic confusion as to what the distinction is between your average software engineer (i.e. programmer) and a data scientist. This is totally understandable, considering the fact that both jobs do involve programming and the term “data science” seems so much like the term “computer science”. However, the two differ in some significant ways.
People in the tech world love to speculate on the future structure of the corporate IT department. While we cannot know precisely how this change will manifest, there are undeniable trends towards a more engaged and decentralized IT presence in organizations. This may very likely end in the elimination of the IT department as we know it.
Companies often find themselves wondering whether or not they have big data and questioning whether they even need business intelligence and predictive analytics to improve their business strategy. The reality is that you probably have more data than you think you do, but that the systems are not in place to make it useful.
It is important to remain aware of the fact that making data work for you is as much about people as it is about technology. Dataspace has learned a lot about end-user engagement with predictive software and business intelligence infrastructures over the past two decades. After all, it is not the products but the user of these products, the guy or gal who makes the day-to-day decisions, which ultimately determines whether or not your organization uses data effectively.
By now, we all know that big data and predictive modeling are at the heart of any successful and competitive corporate strategy. But making data-driven decisions means more than just selecting software or implementing a BI system; it means making sure the people in your organization understand their roles in applying these systems effectively when it […]
If you’re like me, you’re an exceedingly attractive, 50-something data geek with a love for aviation history who’s an amazing ice hockey player. You also spend a lot of lunches eating a sandwich while studying new technologies. This kind of on-the-cheap, self service training helps you keep up with changes in business intelligence / data warehousing / analytics / […]
The Lamest BI Requirement – And it Won’t Go Away! Want a sure path to failure in BI and data warehousing? Don’t solicit requirements from your users. Want a second path? Settle for the requirement, “Just give me everything (JGME) and I’ll figure out how to use it when you’re done.” I’m over 25 years […]
Assessing BI & DW Systems A decent (and fun!) chunk of our business is assessing organizations’ business intelligence and data warehousing capabilities. In assessments we meet with business executives and IT staff to discuss what the business needs, and will need, from BI. We then contrast that with what the organization actually has at its disposal. […]
Looking back on the work we’ve done over the past few years I’ve come across an interesting point: while companies may have mature data management organizations (DMOs), few of these DMOs have a set of principles behind their data management visions. In other words, they’re building data management infrastructures and tools without a clear sense of what they’re ultimately […]
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