It is very much undeniable that beginning with Big Data could disturb even the most sophisticated organizations, which could lead to a whole lot of confusion as well a plethora of money spent in the wrong places. It could lead to your organization to hiring a few quant big data analytics which could further mess up the situation. However, if you know how to begin with the whole ordeal, you wouldn’t even need to make use of these professional services, especially if the platform of your choice comes with some predefined and pre-configured modules.
Interesting enough, if the platform you chose is good enough and supports a massively parallel process (MPP) architecture, you might even be able to take complexity out of the analytics. Also, mesmerizing pattern matching capabilities as well as predictive analytics capabilities will be easily handled with the help of the right platform. So you need to do the following:
Identify the right platform
When looking for a suitable Big Data Analytics platform, you must look for automatic parallelization in a platform, along with full embedded processing. At the same time, it is very important that the platform of your choice utilizes the resources to their full potential. However, it will only be conceivable if the data loading procedures and capabilities are parallelized. In fact, choosing the platform also requires automated backups as well as their easy recovery to their previous state. Last but not the least, the platform of your choice must be easy to install and configure as well as upgrade. It should ensure that the whole platform will undergo parallelization if required.
Some important considerations
If you have some conventional data warehouses or RDBMSs deployed at your system, you should check if the platform of your choice could be easily integrated with them. If they don’t connect with your existing tools then you should look for some suitable connectors for carrying out effective and efficient Big Data Analytics. That said, once you have the right connector in place, you shouldn’t worry about what is going to happen after the deployment, all while considering the analytical richness of the reports, which cannot be ignored under any circumstances. Of course, if the platform if your choice fails to meet your analytical requirement then you might be choosing the wrong platform after all.
Be very cautious
Finding the right platform might be very helpful for getting you started with Big Data Analytics, but you’ll only be as good as the insights you derive from the data. For instance, you must make sure that the platform of your choice returns the same result as it did for the others. What it will do is provide you with great analytical insights. That said, while some consider the existence of MapR in the picture an essential but the abrupt rise in adoption for SQL in Hadoop solutions has rendered the Big Data playground very much different and dynamic for many organizations. So be very careful when selecting a Big Data platform for your organization.
In order to begin with Big Data Analytics, one must tread very carefully looking for the best possible platform for their organization.
Big Data Analytics 101 