Data Science and Data Analytics

The rapid growth of data science and data analytics has forcedly made companies and organizations buzz in searching for professionals (who can deliver at the best status) in the data field.

The data field, including machine learning jobs, will doubly increase in the next few days and that is why the need of the people who have knowledge and experience about it will come to reality in a matter of time.

But before then, some of the genius researchers like IBM have predicted over the years that there will be an increase in data jobs in the United State as the particular field keeps growing higher daily.

Let’s dive into Data Science first before moving to other.

Data Science

Data Science is the process of designing or implementing a very big/large data scale to an understandable, easy-to-use, or desired view (possibly with lots of views).

A Data Scientist collects and obtains data from different kind of possible sources and then integrate the gathered data using machine learning, analytics (either predictive, sentiment, or factual). The data obtained will be used to get/extract particular needed information. In short words, the Data Scientist obtains data to achieve certain information from the result.

Data Scientist applies a logical understanding over an analysis of data which they used to predict to achieve a clear and accurate insight. The business management will then use that insight of prediction by Data scientists to decide their business way forward.

How To Learn Data Science

The data science field has some basic knowledge that one must walk through to learn and understand and also become a data scientist. There are three things you must never ignore throughout your journey in data science. These are analytics, programming, and also domain knowledge.

Going deep through these basics knowledge of data science is much important. Here are the basic knowledge of learning and becoming a Data Scientist;

– Learn Python, SAS, R, Scala

You must learn, understand and become at least an average expert in these components of data that includes programming languages and statistical software. They are the first and most relevant basic of learning data science.

– Learn SQL Database Coding

It is a programming language that is purposely for data management (designing, implementing, and managing).

– How to design and manage not-yet organized data, like data in a visual content format or even on social media. In this case, you must be able to extract and design data from that’s in any kind of format to your desired or required format.

– Ability to understand every single function of the structural part of analyzed data.

– Learn how to use, implement and handle machine learning concerning any kind of data science field.

These are the most important aspect of learning Data Science. Now let’s roll into Data Analytics.

Data Analytics

Data Analytics is a process of figuring out a descriptive design of data with insight and possible conclusions or predictions as an outcome.

While Data Analyst is a person who put data analysis into the reality of visualization. This set of people must have background knowledge of statistics, the creation/building of databases, and the concept of putting data into visualization mode.

How To Learn Data Analytics

Just like Data Science, this also has its basic knowledge which you must pass and learn if you are willing to learn.

What basic knowledge means here is a background that will allow you to learn and explore the Data Analytics field. The following are the basics;

– You must have a knowledge of Mathematics related to statistical data.

– You must be an expert or experienced user of R or Python (the core programming language for data-related).

– Data wrangling

– Understand PIG/ HIVE