Making Sense Of Big Data

Data makes the world go round. Well, it’s actually the World Wide Web but it is essentially where everyone is now. From ordinary individuals of all ages and walks of life to big businesses and organizations, we input so much data on the web. This information, in turn, is utilized by businesses with online platforms to target their customer base. While not all the time it is always for business, people keep on sharing data on the web and the amount of data circulating online is not always used optimally.

Take the case of enterprise data. They are so widespread but you can’t easily relate the data as one. It takes a lot of work understanding what all these big data is all about because you have to narrow down your search and make a thorough review of individual strands of data to make sense of it. Extracting and analyzing these data is already tedious in itself and the entire process takes longer to finish before you figure out what the data you have actually means. There are also a lot of loopholes that need to be considered especially when data is released to customers or third-parties but things may turn for the better with the continuing progress with artificial intelligence.

Life would be simpler if everything were in one relational database, but that's not practical. Enterprises have too much data.

So data gets spread among different databases, some by department, others by function, often with different schemas and degrees of data checking.

There are lots of tools for low-level checking of fields and schemas. But what if you want to understand a complicated relationship between, say, customers of a certain region, purchasing some range of product quantity, and want to understand how their service calls have changed over time?

That will become a major data extraction and analysis problem, starting with figuring out where the data is - probably in several different group databases - and tying all the numbers together. It will take weeks, and you'll probably have to set up another database. Painful at best.

(Via: https://www.zdnet.com/article/startup-aims-to-turn-enterprise-data-into-information/)

There are certain AI technologies geared to making sense of big data to help humans have a better grasp of what the figures and data are all about. The best promise of AI is the part where this process can be automated using special software so that specific data can be retrieved quickly and with little effort from your end.

As we all know, no science is perfect. However, if you are involved in a big business and deal with big data problems all the time, this new technology is worth looking into because who knows it may actually work.

The data revolution of the past decade has transformed how businesses reach out to prospective customers, manage supply chains and provide services. But just as businesses become more reliant on data, governments have started to regulate the use and flow of data. While these policies might be critical for privacy protection and ensuring national security, they can create substantial costs for businesses, finds a new study by Martina Francesca Ferracane of Hamburg University and others.

The authors argue that in today’s economy sectors such as management consultancy and financial services rely heavily on data. Therefore, policies that restrict the use and cross-border transfer of data are likely to reduce the efficiency of these sectors. Such costs and inefficiencies are passed on to other businesses and then to consumers.

(Via: https://www.livemint.com/Companies/Md0H3SnbEvPWc3NhAJz6sM/SnapFact-Data-regulation-proves-costly-for-businesses.html)

The most pressing concern here is in regards to data security and privacy. These numbers and information do not merely just represent a problem that needs to be solved but pertain to certain individuals or corporations who aren’t always aware how their data is utilized by companies who have access to it. These limitations also affect big data analytics and use and greatly affect efficiency but you can’t always rationalize that the end justifies the means.

We may be a long way from truly finding the right formula in managing big data and data security but at least these factors are still taken into consideration, meaning customers aren’t always that vulnerable on the web.

If big data puzzles many, so does data loss. It can trigger panic attacks among users especially when a backup is not put in place. Learn more about how you can overcome the challenges of data loss by knowing data recovery services such as https://www.harddriverecovery.org/mac-data-recovery/ and https://www.harddriverecovery.org/raid-data-recovery.html for computers and servers alike.

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