Scroll Top
Seerapalayam Village, Coimbatore – 641 105

Data Science and Analytics in Engineering: Leveraging Big Data for Smarter Solutions

Leveraging Big Data
Concept of cyber server cloud data storage. Cloudscape digital online rack service for global network. Web database backup computer safety infrastructure technology

Data science, analytics and big data are three important technologies that run during the generation of data. The main goal is to provide the data which are essential to make better decisions. As always, companies biggest assets are the data and when it is used effectively, then it yields lots of benefits. To establish a business presence, it is now mandatory to know how companies properly make use of those unstructured data.

The b tech computer science colleges in Coimbatore now clearly blend with the current demands of the business by implementing the required courses. Let’s discuss these three concepts and their benefits to acquire smart solutions.

What you should know about data science?

It is a broad concept that collects data from various external sources with the support of machine learning, artificial intelligence, predictive analysis and sentiment analysis. The purpose is to offer accurate predictions and insights to the business or companies which are helpful to make decisions. The best example of data science is the Google search engine where to deliver the best results in search queries it uses data science algorithms.

Steps to process of data science:

  • Creating a set of research questions.
  • Gathering information from various independent sources.
  • Preparing raw data for analysis by filtering and cleaning.
  • Creating AI and ML models for extracting massive amounts of data.
  • Creating tools to monitor and assess data accuracy.
  • Creating dashboards, charts, and other data visualization tools.
  • Putting software into place for automated data collection and analysis.

How do data analytics and business work together?

It is to analyze the large amount of data collected with the support of software and algorithms that can answer questions and derive conclusions. Businesses used data and data analytics used to analyze those raw data to get required insights for the business.

Process of data analytics:

  • Detect what the informational needs are.
  • Get data from primary and secondary sources
  • Cleansing data for analysis.
  • Analyze the data into patterns
  • Translate them into insights
  • Offering the findings to business

What are the data analytics types?

  • Descriptive analytics to understand, evaluate and describe the findings.
  • Diagnostic analytics to understand the “why” behind what has happened.
  • Predictive analytics is to find the history or past data trends to answer the questions of future trends.
  • Prescriptive analytics identify the actions that business or companies consider for achieving the goals.

How do data analytics work in companies?

  • Data engineering team ensures that data can be accessed by a centralized data center.
  • Analytics engineers by modelling data in a way that gives consumers the ability to find the answers to their questions, we can provide clean data sets to users.
  • Data scientists have to extract value from the data, use machine learning algorithms.
  • They mostly use the Data Assets produced by Analytics Engineers to produce insights that can be put into action.
  • Business analysts collaborate closely with the business clients to collect the specifications for creating dashboards and other visualizations that support decision-making.

In this article, you can find the data analytics concepts when you consider pursuing computer science or any other related fields in the best engineering colleges in Tamilnadu. And there are various career prospects for the data analyst you can prefer to work in the future.

What you should know about big data?

It is the field that can analyze important data that can’t be processed with traditional software. Most big data is able to analyze three types like unstructured, semi-structured and structured data. So, big data control software, hardware, process techniques and database technologies.

Steps involved in processing big data:

  • Establishing the reliability and safety of distributed systems for data collection.
  • Constructing a massive data processing system to hold and handle huge quantities of data.
  • Using big data tools to process the data.

Are data science and big data the same? They are not the same terms but consider big data holds a large part of the unstructured data and requires analysis. At the same time, data science extracts the information a company or business requires.


This article gives you an overview of how data analytics, data science and big data work in organizations to extract the data required for the business to make decisions. The insights and predictive analysis give an answer to what is next. This basically helps to analyze the growth of the company and techniques to move forward.

In the engineering field, data analytics is crucial and most companies have to adapt to the cloud technology and apps to understand their audience better and the digital touchpoints of users.

Today, these are fields where experts are required to understand the data and business needs. So, the Top Computer Engineering Colleges In India focus on how students can merge with the trends and upcoming technologies.

Related Posts