As technology grows ever larger and the usage of technology grows ever broader, the collection of data is increasing exponentially. Not only is there more data to collect, store and manage, there are far more varieties and sources to worry about too.
Think about all the places where you gather information today:
• Customer requests on your websites.
• Mobile application input from smart devices.
• Point of sale data.
• Daily information from internal management.
• Analytics gathered from recorded metrics.
• Logistical information piped in from automated detection, sensing and recording devices.
• Financial information.
It goes on and on. And how about the types of data that you may deal with. Data comes in text form, audio and video as well. It’s daunting to even think about, isn’t it?
How do you handle it all?
Are you a growing organization who’s been relying on MySQL or Oracle to handle your databases? Are you finding that your data sets, both structured and unstructured are growing beyond these systems’ ability to manage in an effective and timely manner? Are your databases connected to RAID arrays containing thousands and even millions of files?
As if all this weren’t bad enough – often there are multiple data sets in multiple locations, making proper management even more difficult. The ability to correlate all of this information efficiently is critical.
Luckily, “big data” solutions offer a distinct advantage and solution to the problems of growing organizations who are growing out of their original data shoes. Distributed Big data systems based on solutions like Hadoop allow for the complete organization, storage, retrieval and management of structured and unstructured data sets and related information.
How do you know when it’s time to switch?
Making the decision to port your data over to a big data solution is important. The trick is knowing when the time is right.
The time to make this decision, certainly, is before you know it’s absolutely critical. Never dig your well when you’re thirsty, as the saying goes.
One indicator is the speed at which you are able to retrieve information. If, for example, the request to retrieve data from your current database seems to take an inordinate amount of time – and this is a common occurrence, your data sets are too large for the current system to handle.
This can cause major problems when attempting to access customer information during a transaction, or when running daily financial batches takes many hours and uses so many compute cycles that nothing else can be accomplished.
Another general rule of thumb is when your data sets begin to grow into the terabyte range. This is somewhat arbitrary, but certainly if multiple hard drives are required for a single database, you are either approaching or are already in the realm of big data.
It’s a tricky decision, and it’s not a bad idea to consult with a big data specialist who can analyze your current data sets and recommend solutions – or not. Remember, in a digital world, information is king!