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UNDERSTANDING PATTERNS WITH DATA ANALYTICS

Patterns. Patterns are literally everywhere. From our simple surroundings to nature, from complex algorithms to something as simple as the locks on our phones, the world just cannot exist without patterns. It simply cannot. Take for instance- the golden ratio. A pattern found in every aspect of nature. Some may say it’s just coincidence, but even coincidence happens once or twice. Patterns are what bring order from chaos.
Patterns and analytics

The question of any relation between analytics and patterns is relatively easy to answer. The field of analytics deals with nothing but data. However, with the advent of the Internet and all tasks, shifting online, the amount and variety of data generated and collected on a daily basis is huge. Sorting and searching for a particular piece of information in this heap is nothing short of a nightmare. This is where patterns kick in to make life easier. Once a pattern is noted, or observed in relation to the requirements, finding it is not a big deal then.

The need for analytics Unlike analysis (the counterpart of analytics), which deals with past events, analytics focuses on the details and future predictions of an event, which is a much more vital aspect for it deals with the in-depth analysis of the actions that lead to an event, and how the same event will unfold taking different possibilities as inputs. Basically, it deals with future planning rather than cringing about the past. It handles the past events graciously and takes measures to either prevent it from happening again or devising and implementing some safeguards to minimize the damage should the event strike again.
How does it function?

Today the world is surrounded by a large number of powerful computers capable of performing tasks at speeds and complexities that are beyond the scope of imagination. Furthermore, to perform these complex calculations, we need sophisticated algorithms, and numbers & statistics as inputs for these algorithms.

Once these two essentials are procured, all that is left is to feed them into the computer systems or trained models (that learn themselves in every instance of generating an answer to a query), and sit back and watch them come up with solutions to all kinds of problems. Sometimes, answers to queries come up which could not even be thought of.

The Expanse
The study of analytics has seen its roots spread into many core industries where it plays one of the pivotal roles in its functioning if not THE pivotal role, such as in the field of medicine, business, marketing, banking, security, cyber security, software designing, SEO and of course, needless to say, computer sciences and mathematics and a countless more.
Challenges As the field is still relatively new hence obviously it has some loopholes in it, that pose a challenge to it at different steps on its way of operating. The biggest challenge it faces is when it is used alongside big data. Finding and generating patterns in a colossal pool of totally random data is not at all easy. Unstructured data also hinders the proper workflow of any task and its analytics is also not something that happens as easily as one would want.

Resource Box
As the field of analytics is in its prime with such heavy tasks to perform, naturally, the need for expert and trained professionals for the same is also high. So in case, you are pondering over choosing this field, get a Data Science Course right now.

https://360digitmg.com/course/certification-program-in-data-science

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