Data scientists are pushing the boundaries of analytics

Data science is a boon for growing industries. Before data science was established, it was difficult for the companies to sell products according to public demand and as a result they could not grow a great deal. But, the emergence of data science brought new revolution to industries by pushing the limits of data analysis. Data science brought new tools which made data analysis simpler and more accurate. Nowadays, data scientists are making a fortune because their demand is rapidly increasing in the market. The minimum salary a data scientist will earn is about $95,000, which is higher than most other professions.

·        Defining data science-

Data science is the discipline which unifies statistics, machine learning, mathematics, computer science, information technology in one field to understand and analyze the data in an effective manner. This science is utilized to discover hidden information from large volumes of data. Data science gives insight into improving the products and the business strategy.

·        Data scientists improving data analysis –

A data scientist goes through certain processes daily to accurately analyze the data and find better solutions to the problems.

1.      Understanding the problem-

The first work of the data scientists is to be thorough about their goal. They study the sales process, tiers of service, targeted customers and try to have a grasp over the domain.

2.     Data wrangling-

The data scientists are then provided with huge databases. They have to perform data cleaning with proper focus because it will involve finding missing values and correcting the errors.

3.     Exploring the data-

Now, the data scientists are trying to find some hidden patterns from the collected data. They use bar graphs, pie charts, histograms and many tools of excel to represent the data visually.

4.     In depth data analysis-

At this point, machine learning turns out to be an effective method to analyze the data deeply. Different data points are marked as feature vectors and labels converting them into suitable inputs for machine learning. The data scientists use programming language like python to create algorithm which will be suitable for a predictive model. Through supervised learning, important information from the input is extracted. Tools like logistic regression, binary conversion are used according to requirement.

5.     Data visualization and communication-

The final work of a data scientist is to represent his findings in a format which will be understandable by the executives of the company. He will have to communicate the important information extracted from the data as well as the predictive analysis. He will have to find the missing parts in the process and suggest proper measures to correct them.

 

·        Top data science tools-

Data scientists are trusted by most of the companies because they use sophisticated tools to arrive at conclusions. Some of these tools are SAS, Apache Spark, BigML, D3.js, MATLAB, ggplot 2, Tableau, Jupyter, Tensor Flow and Weka.

According to Glassdoor, data scientist is the highest paying job in the U.S., which shows that as a data scientist you will be making a good salary to live on. 

Resource box

Excelr is offering a Data Scientist Certification with cutting edge education facilities. The educators are eminent professionals in this field and can build your skills both theoretically and practically. So, do not hesitate and sign up for the course.