7 Big Things Big Data Can’t Do – Alone!
Move over data mining. Big data has emerged as the next big thing in data analysis and management. Pundits hold this thing in such high regard that organizations adopting it for the very first time come in with extremely high expectations – often too high. While there is plenty to gain, nothing is guaranteed. In order to reap those lofty benefits, organizations must put in the work.
With all the buzz in the air, it’s fairly easy to approach big data with expectations that are a bit unrealistic. But that’s why we’re here. To break down seven monumental tasks you shouldn’t expect big data to do without a little help.
1. Automatically Solve Problems
The experts often say that before you invest in big data, you should determine which business problems you need it to solve. That’s sound advice, but no matter what technology you’re able to get your hands on, always remember that it’s the people using the tools who make the magic happen. Therefore, if you want spectacular results, you need to make sure you have your best people on the job, in addition to identifying your needs.
2. Simplify Data Management
From Amazon to IBM, vendors proudly boast how their big data solutions make data easy to capture, visualize, and manage. All that “easy-to-use” stuff sounds good, but the fact of the matter is that taming mountains of data can be extremely challenging even with the most user-friendly tools. Policies built around archiving, retention, usage and other aspects are needed to bring simplicity to the process.
3. Clean Dirty Data
Despite their limitations, relational database management systems like MySQL and SQL Server do an amazing job at improving data quality right off the bat. Big data – not so much. Although there is tons of automation involved, organizations are often tasked with manually cleansing unstructured data before feeding it into their analytics platform.
4. Calm Security Concerns
It’s no secret. The more sensitive data you have at your disposal, the bigger target you become for hackers and security threats. Even companies who have struck relative success with big data are finding it difficult to provide secure access to the huge sets of data streaming through the organization. The fact that access is needed across multiple departments and devices only adds to the security conundrum.
5. Accommodate Existing IT Skills
If you think your IT manager or database administrator is equipped to handle a big data infrastructure, prepare to be rudely awakened. Managing data with this level of volume and complexity calls for a special skill set and according to market observers, specialists who possess them are limited in quantity. As a result, you have many organizations assembling big data personnel comprised of data analysts, software developers, and computer systems engineers.
6. Eliminate Old Systems
One of the many cool things about big data is that it affords the opportunity to consolidate your data and get rid of old information that holds no business value. The same can’t be said for old systems (CRM, email marketing, spreadsheet applications, etc.). If anything, those systems will become even more valuable when it comes time to unify your informational assets and make data-driven business decisions.
7. Promise Positive Returns
Big data offers a number of benefits, including a better return on your technology investments. However, that doesn’t necessarily mean that you’ll immediately see huge gains in revenue and profits. Gauging success can be difficult outside of increased sales and conversions, so it pays to establish new metrics that allow you to better measure the ROI you get from big data.
As you can see, big data isn’t exactly the miracle worker it often appears to be on the surface. Having said that, it can deliver the outcomes you desire with a little planning beforehand and sound execution once your system is up and running.
by Big Data Companies