Dealing with a large amount of data should never be treated as a trivial matter, whether you want to move it, analyze it, upload it, download it, etc. No matter how big your organization may be, you can never be too careful with big data.
There are a number of things that can go wrong if you’re not careful. Just making a single mistake can lead to dire consequences. Here are some mistakes you’ll especially want to avoid:
Lacking a specific business objective – What exactly does your company hope to achieve with all that data? Data by itself yields no results. While it can tell you plenty of information about consumers, competitors, products, employees, mobile testing analysis, and so forth, that information is useless if it is not being applied to achieve clearly specified objectives taking your own business contexts into account.
Not keeping the data up-to-date and ensuring its accuracy – What use is old, irrelevant information? How is that going to help you achieve anything? Your organization must implement the process of regular updating, validation and standardization. Make sure you have the right software and tools to maintain and measure the quality of every last piece of data.
Failing to migrate properly – There are so many things that can go wrong when it comes to moving a large amount of data: you could use the wrong tools, fail to test the migration process, lack a timeline,exclude the the right departments from the process, include the wrong departments, etc. Even if you don’t have to move it right now, there will likely be a time in the future when you must. Carefully plan the migration process, use the right aggregation tools and consider which departments would be ideal for the project.
Leaving big data problems in the hands of data scientists – While statisticians and math experts should certain be included in your organization, there is more to big data than numbers. According to Forbes, data scientists are “only one part of the complex” team required to bring your business value. When there are problems with the big data, you must also involve your marketing and development teams in the solution process.
Having a mindset that you should never delete anything – One major big data mistake is keeping it all forever. Do not be one of those organizations with a “keep everything” attitude. If data is obsolete, get rid of it. The cost of storage and maintenance will only continue to increase if you do not. Prioritize information. Is it really necessary to keep competitor research notes your business conducted several years ago on a competitor that is no longer even in business? Or manual testing notes from 2006 when mobile internet was in its infancy when you can now use advanced test automation technology in 2016? It’s just a waste of money and space.
Not breaking it into small pieces – The vast nature of big data can seem very overwhelming. Huffington Post explains that data should be considered “in bite-sized pieces” in order to be actionable. Try to organize it in a way that makes it more digestible and useful. As a result, goals will be easier to reach.
To truly realize the promise of big data analytics, you must have the correct tools, relevant data, and highly trained individuals who specialize in extracting value from the ocean of data and communicating it in a clear, compelling manner to those who are in a position to take relevant action on it.
