Big Data has been the âBuzzâ word for a number of years and despite the increased usage of the term in our vernacular, many of us are still a little unsure as to what it really means.
Microsoft. âBig data is the term increasingly used to describe the process of applying serious computing powerâthe latest in machine learning and artificial intelligenceâto seriously massive and often highly complex sets of information.â
Large data sets have been around for a long time; however the speed at which itâs now being collated and the complexity of the data being recorded is an inevitable outcome of the enormity of information being collected on a daily basis.
âBig Dataâ is now more of an action, rather than a talking point amongst many businesses and to this end, we are seeing more and more companies internalise Â the âBig Dataâ question with a view to learn more about their own existing data to find solutions for it to be more effectively monetised both internally and externally.
The most common misunderstanding surrounding the âBig dataâ topic is the belief that more data is superior to less. To some extent, there is some truth to this, however a more relevant question to ask would be: âHow much of the data is âhigh definitionâ, âuseableâ and can be converted into real insights and finally, can it be monetised effectively?â Â
Data plays a vital role within the RTB Ecosystem; itâs the driving force behind its accuracy, itâs efficiency and ultimately, its profitability. As briefly mentioned in my previous article-Â http://bit.ly/1eXNOGQ, Data within
Similar to the increased number of the DSP technology vendors as compared to only a few years ago, the data management platform (DMP) space has become just as competitive. Â The Â likes of Adobe, X plus one, LOTAME and Blue Kai all have strong product offerings and are most certainly leading the initial rise within the DMPâs arms race.
Take some time to review Aprilâs 2013 Foresters report on âThe Forrester Waveâ¢: Data Management Platforms, Q3 2013 reportâ³Â â This is the first report to thoroughly evaluate the current data management platform (DMP) vendors globally (as of April this year). Â
A number of companies are now in the process of developing a product offering and/or leaning their businesses toward the âDMPâ product market. Some are already claiming to have a fully functional âDMPâ product to release to the market. In light of this highly accelerated rise of DMP products, in my view; to claim the product as a DMP is one thing, but to actually have the required infrastructure, the data science behind it, the technical real-time responsiveness, the precise functionality and finally, the business model that aligns with youâre clients business and its needs, can often be a hard relationship to come by.
As more businesses decide to drive change through their own proprietary data monetisation strategies, the thirst for strong data analytical talent will continue to skyrocket throughout RTB, amongst many other industries.
The introduction of RTB and Programmatic Trading to the world has really boosted the profile of the âData Scientistâ thus highlighting the embarrassing shortages we have within this skillset. We are now in the age of the âPetabyteâ and I am pleased to see that universities around the world are now finally offering Data Science / Machine learning focused degrees or double degrees with Computer Science Majors.
If you are a Data Scientist, Analyst, Mathematician or Statistician and want to know whatâs available out there, then please get in touch
This topic is one that requires much discussion, and I welcome your thoughts. You can comment here on the blog, or email me directly-Â email@example.com