The Generation of Data

An introduction to data, you have always seen those beautiful advertisements all over the internet whichever website you visit and felt that someone just knows what you want its just because we have it all save somewhere in the giant server stored to be harnessed by the everyday marketers. Let’s understand in a bit depth what it takes to be able to identify what you want and looking for is in your previous searches and things you have browsed on the net. The big corporation have high loads of data which they have analyzed by complex algorithms to keep the traffic that is you and me engaged on the internet. Albeit it is but obvious the data we provide them is being used to keep us busy, now it is time for us to benefit from it. Everyone, especially the entrepreneurs shall buckle up and get ready for the opportunities which we talk about in the last blog post ‘The Renaissance of New Entrepreneurs’. I will walk you through this opportunity both as an individual professional and from business perspective.

There are lot of job opportunities as well as product building capabilities in the field of data. Today we will talk exclusively about data analysis and build around it. So, let’s just get started, to form interest lets see the jobs in this field pays between a sum of $45K to $130K according to builtinnyc.com. We can from this fact come to conclusion that it is one of the biggest and best way we learn, with the jobs and the realm of self-employment on the rise it is important for you to dive into this. The depth of the potential is unleashed and it is beneficial to explore before it is exhausted. The dependencies of machine learning, data science and artificial intelligence on data and its analytics that gives insights which was ver thought of.

The most recent and relating example can be that of the analytics given by the medical and research fields on the issues in correlation with pandemic covid-19 virus. The linearity in the graph can be seen here and that is pretty accurate.

Many governments have always tried to control the data and your life. They use data to predict public response to many of there actions and try to mitigate the effects accordingly. Out of home media, Advertisement industry and the online advertisement campaigns are all based on the data manipulation done at different levels, one of which is analyzing it. For example, where and when to show a particular advertisement by analyzing demographic data to create maximum impact and minimizing the budget i.e. optimizing the complete flow by generating conversions is the main motive.

Data analytics can further be divided into types:

1. Descriptive analytics is responsible for describing what has happened over a given period of time.
2. Diagnostic analytics which focuses more upon why an event took place involving diverse data and a bit of hypothesis.
3. Predictive analytics as the name suggests it moves towards what is going to happen.
4. Prescriptive analytics which gives you the course of action.

Data analytics is considered important because it can provide in depth answers to certain questions like never before optimizing the performances that’s why corporates are let you store data for free so they can use it to get insights making business decisions better and easy, albeit it has a lot of scope for improvement. So, you rightly guessed the data you store for free on the web is not out of generosity of the companies like google, Facebook and amazon but for a mutual benefit.

Data is a wave in the ocean which is your opportunity to ride the tide because fields like data analytics are the science of converting raw data into human consumable and understandable form. These techniques and processes are further converted to algorithms which can be reused and scaled. Lastly, the potential in this field was discovered long ago but is still bearing fruit which can be enough to state this is not going to go into the drain soon enough.

I would like you to comment below about what you think of data analytics and if you are willing to dive into the ocean of data then which industry you find the most suitable. Do not forget to share it on social media.