Browsing "Older Posts"

Data

Why You Should Not Keep All Your Data Forever

By Jessie L. Morgan → Friday, September 6, 2019
For some reason, there are many businesses that believe their data should be secured and stored forever, after all, someday they might need it!.

It really doesn't matter what your company policies and procedures were for keeping all your data from back in the 90s, any reasons have become mute in this day and age.

 The data you are so desperately trying to keep is obsolete, outdated, and of no value. Any information that was possibly in old data has probably been recreated in new data, so clean house.

 If you are someone who loves to collect and store images of animals, whether cats, dogs, horses, tigers, etc. You probably have every shape, size, and breed possible. The point is, after a few years, you are going to discover this data holds no value, so why keep it?

Big Data

Preparing Data For Success

By Jessie L. Morgan → Friday, June 28, 2019
Many businesses will try to find answers to data issues and end out failing. This could lead to approaches that will harm the market on getting the right solutions for data. To create greater success, we will discuss some of the leading problems and how to overcome many of these challenges.

Preparing Big Data For Success

The Difference Between Data & Big Data

By Jessie L. Morgan → Saturday, March 16, 2019
As I'm sure you are aware, data is gathering and processing information and software in a timely manner. Big data is information that is enormous in volume and very complex. This big data cannot be collected, managed, or processed in a timely manner.

Big Data vs Data

Maybe you are interested:

There is no clear line between what is considered Big Data but it's usually in multiples of petabytes and enormous projects in exabytes.

By rule of thumb, big data is defined by the 3 V's:

- Volume: an extreme level of data
- Variety: the number of different kinds of data
- Velocity: the amount of data that must be processed and analyzed.

Data that is established as big data comes from various places including social media, websites, mobile and desktop apps, scientific data, IoT (other devices in the internet of things, and sensors.

Big data comes from a variety of components that allow a business to put their data to practical use and solve any number of problems. This can include the IT infrastructure for supporting data, applied analytics, the technology for projects, various skills, and the actual use to make big data clear.