Why should you learn Data Science in 2019?


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In recent times, Data Science, an emerging technology, has perhaps been the most discussed term in the Information and Technology industry. Data Science has become one of the preferred career paths among IT professionals.

Today, more and more organizations, ranging from small scale to large enterprises, have realized the importance of Data science and are implementing its capabilities to successfully scale up their business to new heights.

As the Data Science is getting more attention, this blog is focused towards discussing some of the valuable aspect of data science which can be helpful to our readers.

Some of the concepts included in this following discussion are as follows:

  • What is Data Science?
  • Why we need Data Science?
  • Tools required for Data Science
  • Data Science career outlook
  • Applications of Data Science
  • Learn Data Science online

Let us start with finding out the answer to the question, “what is Data Science?”

What is Data Science?

Data science is the discipline that uses the scientific methods, domain expertise, algorithms, knowledge of math and statistics to extract meaningful insights from data.

The emergence of new technologies has resulted a huge increase in data. This has provided an opportunity to analyze this data and derive a meaningful insights from it.

Analyzing such data requires some special experts like Data Scientist, who specializes in Data Science. These Data Scientists use various statistical and machine learning tools to analyze the data drawn from different sectors like social media, e-commerce sites and Internet searches, etc.

Therefore, we can understand Data Science as the study that involves extracting meaningful information from large amount of data using various scientific methods, algorithms and processes.

Why do we need Data Science?

Now that we have understood what Data Science is, let us discuss why Data Science is important.

Today, Data Science has become a significant factor for the organization’s growth. It helps them to make a better decision to enhance their business.

Organizations with the help of Data Scientists derive the meaningful insights from large amount of data that allow them to analyze themselves and their performance in the market.

Data Science helps the organization to understand its customer requirements better and provide them good service that will help them to grow efficiently.

As more organizations are implementing Data Science into their business strategies, it has resulted in creating a number of jobs in the Data Science field.

Tools required for Data Science.

Now that we have understood why we need Data Science, let us move on to understanding the tools involved in Data Science.

Data Science has various tools, some of which are discussed below:

1) R programming language:

  • R is a programming language widely used by Data Scientists and many organizations for data analysis
  • R language possesses the feature of Object Oriented Programming Language
  • R programming language is also used for statistical analysis, graphics representations and reporting.

2) Python programming language:

  • Python is an Object Oriented Programming Language widely used for Data Science and software development
  • Python works on different platforms like Windows, Mac, Linux, etc.
  • Python can also be used to develop several applications like web applications, Graphic User Interface based applications, Scientific and numeric applications, etc.

3) Structured Query Language (SQL):

  • Structured Query Language (SQL) is used to create new databases, tables and views. It is used to insert and update records in a database
  • Structured Query Language (SQL) is also used for deleting records from database and also to retrieve data from a database
  • Data Scientist uses Structure Query Language (SQL) for managing and querying data stored in the database.

4) Hadoop:

  • Hadoop is an open source framework used to store and process big data
  • Hadoop provides Big data analytics through distributed computing framework
  • Hadoop provides flexibilities as the users don’t need to preprocess the data before storing it. You can store as much data as you want and decide later on how much of it you want to use.

Data Science career outlook

Data Science professionals are in high demand in today’s IT industry. Some of the roles associated with Data Science are as follows:

  • Data Scientist
  • Data Engineer
  • Data Analyst
  • Machine Learning Engineer
  • Statistician.

Let us discuss about these different jobs individually.

  • Data Scientist:

A Data Scientist is a professional who deals with structured and unstructured data to derive information from it using various statistical methodologies.

Data Scientists uses different set of tools, techniques, methodologies, algorithms, etc. to extract meaningful information from the data. They help the companies to enhance their business.

  • Data Engineer:

Data Engineers are the professionals who prepare the Big Data infrastructure to be analyzed by the Data Scientist. They work with large amounts of data. They take responsibility of design, build and integrate data from various resources and manage the Big Data.

  • Data Analyst:

Data Analysts are the experienced professionals. Data Analysts query and process data. They provide reports and summarize and visualize data. A Data Analyst performs tasks such as data cleaning, performing analysis and creating data visualizations.

  • Machine Learning Engineer:

Machine Learning Engineers play an important role in Machine Learning model development. They take responsibility from coding to deployment and also for testing and troubleshooting the issues that occur during developing such models.

  • Statisticians:

Statisticians apply statistical theories and methods to analyze the data. They help the organization to enhance their business by providing them the meaningful data.

Applications of Data Science

Data Science has wide range of applications. Let us look into some of the applications of Data Science.

1) Internet search:

Internet search has been one of the major applications of Data Science. Today, search engines like Google, Yahoo, Bing, etc. are using Data Science algorithms to provide the relevant information to the users for their searched query.

2) Targeted advertising:

Reaching out to the right audience is very important for organizations while marketing their products. Data Science helps them achieve this. The organizations are using Data Science algorithms to reach out to their targeted audience with less expense and, hence increasing their business.

3) Develop games:

Data Science technology is also used to enhance the users gaming experience. Machine Learning algorithms are used to develop games which can improve/update themselves when the users move to higher levels.

Learn Data Science online

Data Science professionals are in high demand. Several IT professionals are looking to make their career in this field. Then, where to learn Data Science? There are many answers for this question as there are various platforms available to learn Data Science.

One such platform is Simpliv, a pioneer in providing online courses in Data Science. Simpliv has well designed courses which are taught by industry experts and provide complete knowledge about this field.


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