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Does Analytics Need Big Data?
There’s so much jargon being thrown around these days. Some of it relates to new or emerging technologies that are actually quite independent, but because so many of these names and terms are often mentioned together it only adds to the difficulty that non-technical business leaders have in understanding these technologies and where they might be of use to their companies. "Big data analytics" is one such term. Alternatively, one also hears of "analytics and big data". And then there’s "marketing analytics", "social media analytics", [...]
Business Intuition: a Key Input in Big Data Analytics
I’ve sometimes been asked why it is that there’s so much more emphasis on the involvement of the business in analytics projects, and why it’s any different from the need to involve the business in IT or software development projects. This question is indeed a valid one. After all, no business software would serve its users well unless it was designed to meet their needs. In order to find out what those needs are the developers would need to speak to the business to understand [...]
Six Steps to Big Data Analytics Success – Part 6
Once the model has been completed and validated it can be deployed and used by the business. This is often easier said than done. The business will only accept and use a model if understand it’s value and are convinced that it will help them improve their output. Cultivating a data-driven culture is something that has to be done as a part of the broader strategy of using analytics, and one of the more fundamental ways to help it along is to make sure that [...]
Six Steps to Big Data Analytics Success – Part 5
After identifying the right team, the actual analytics work can begin, and that's Step 5 of the cycle. Step 5: Execute and iterate The above seems like a simple enough statement, but in reality it takes time to produce results. First there’s the implementation of a framework to collect, process, cleanse and integrate the necessary data. If very large volumes of data need to be gathered continuously perhaps a Hadoop implementation may be necessary. Getting the right data in place, and having it scrubbed to [...]
Six Steps to Big Data Analytics Success – Part 4
Once the leader of the analytics project or initiative has been identified, it’s time to put all the required skills in place. Step 4: Get the right team together. The ideal big data analytics team involves a number of skills that can largely be viewed in three broad perspectives – technology, data analytics and business. On the technology side, the right skills are required to work with big data capture (or extraction), storage, cleansing, analysis, and visualization. This also involves selecting, implementing, integrating and managing [...]
Six Steps to Big Data Analytics Success – Part 3
There’s a reason why the previous step (Step 2) recommended reflecting on what types of data might be required and where they could come from instead of leaving it to be something for a newly formed analytics team to run with. Understanding where the source data might lie provides a valuable input towards starting to build a project team. Step 3: Identify an owner/leader for the analytics programme. Although several surveys have revealed that getting into business analytics is high on the agenda of many organizations [...]
Six Steps to Big Data Analytics Success – Part 2
Once the business question most critically needs an answer has been framed, the next thing to do is to take a step towards determining whether it’s actually feasible to find an answer to that question. Step 2: Think about what data might help answer those questions. This is important. Is it data about what customers already bought? If so, what kind of data about what they bought? How many kinds of data? At this point, the thinking should not be constrained by any knowledge of [...]
Six Steps to Big Data Analytics Success – Part 1
A common challenge that many companies face in starting up their big data and business analytics programmes lies in understanding where to start and how to make it all come together. Business analytics requires the application of various skills that are normally found distributed across multiple functions in contemporary organizations. It doesn't help that the availability of new technologies for and techniques is invariably accompanied by new jargon to describe them. So if you're one of those business leaders who is wondering how to begin, [...]