Data lakes may be overhyped, but they clearly represent a new opportunity for enterprise analytics. The danger is that: “By its definition, a data lake accepts any data, without oversight or governance. Without descriptive metadata and a mechanism to maintain it, the data lake risks turning into a data swamp.” Some proponents of data lakes…
Just imagine you put some KPIs in place and instead of measuring and improving performance, they lead to the opposite: A mindless chasing of numbers, resulting in reduced performance.
I recently presented at the Big Data Inspiration Day in the Netherlands, talking about real-life organizations that are using Big Data to get closer to customers, inspire employees, and optimize resources in real time. Here’s an edited-down version of my 15 minute presentation — and don’t forget to check out the other great presentations given…
In business, better-informed decisions often start with a strong appetite for data, followed by a healthy dose of skepticism for it. If available, our collective insight becomes the guiding light for our decisions enhanced by data. In the absence of it—when we are left to decide by ourselves—we seek wisdom in our own experiences to fill the void where we can’t find or rely on data.
Does turning data into beautiful, elegant graphics actually result in a better-informed audience? Is it the most efficient, effective way to get your point across?
There’s no shortage of opinion in the blogosphere on the relative merits of SAS, R and Python for data science.
How do you apply MDM within this new data ecosystem?
What does all this have to do with big data? Well, big data software enables us only to identify correlations between variables. It doesn’t tell us whether a causal relationship exists, let alone which direction the causal relationship runs.
By Gregory Piatetsky, from: http://www.kdnuggets.com/2014/10/cartoon-halloween-big-data-privacy.html
Data analysis is very different than interpretation. Interpreting explains the data but does not compare it for future decision making. Profitability is not created from what we decide for today but what we can forecast for the future.