Importance of Big Data Analytics

Today, Data Analytics is the new Gold mine. Moreover, no industry, business, or government can survive without Data analytics. Data is now the most powerful tool in the hands of companies, corporations, Industries, and others. The progress has been vast and immense in  Big Data Analytics, because of the power of the data and its profitable interpretations. For centuries people have used data to make decisions. However, in the present case, it has gone ahead to a new level because of the use of the internet and Artificial Intelligence. The importance of Big Data Analytics and its uses is discussed in this blog.

Big Data & Analytics

More than 4 billion people use the Internet all over the world. The number of internet users is growing at a high speed every day. Moreover, the Internet and the web have created huge data and also opportunities to analyze this data. For example, Facebook generates 4 petabytes of data every day. This is equal to million Gigabytes, in addition, Facebook uses this data to make profits. Therefore, Big Data is also a gold mine of opportunities. Tap the source and the rewards are amazing.

The benefits of Upskilling and upgrading in Data Analytics are numerous. Today if you are planning to upskill and are wondering about the most suitable course you should take up then, Big Data Analytics is the most popular and happening course to take.

What is Big Data Analytics?

Simply put, Big Data Analytics is the method or process by which Large amounts of structured, unstructured, and semi-structured data also called Big Data, are analyzed.  This data is further interpreted as patterns and correlations. Meaningful information is extracted from such data and used to make profitable decisions. So why is this data so important? This is because the information got out of the data is used to make wise and profitable business decisions. This not only benefits the companies but also customers.

 Data grows at a great speed every day. The volume of data created is so huge that traditional tools and techniques have no capacity to store or study them. However, this data cannot be ignored or discarded as it has valuable information in it. Therefore it is used by organizations to help their businesses. 

Social media, Gadgets, businesses, IoT, videos, and other sources generate large data every day. Since this data cannot be stored, organizations use Big Data tools and techniques to store and manage this data. It is difficult to understand this data by traditional methods as it lacks the capacity. Therefore, it is essential to understand the role of these data tools and techniques in data analytics. listed below are four important characteristics of this data.

Big Data has 4 main characteristics

  • High Velocity
  • Volume
  • Variety 
  • High Veracity

Importance of Big Data Analytics

Why Is Big Data Analytics Important?

Today every company or industry E-Commerce or social media depends on analytics to improve and make profits in their business. Companies that depended on big data analytics have performed nearly 25% better than those companies which did not use it.

 Also, the importance of big data cannot be ignored or underestimated. However, there are many reasons why big data analytics is important. First and foremost, the information is reliable. Small businesses also make use of this technology as it helps them to compete with bigger companies. Moreover, it helps companies to make better pricing of their products and cut costs. In addition, Predicting the market, business, and Industry trends are its important functions.

Top reasons why big data analytics is important

  • Makes businesses efficient
  • Improves Pricing
  • Increases sales and loyalty
  • Helps companies to hire suitable employees
  • Reveals shopping preferences of customers
  • Predicts the future outcomes 
  • Provides solutions to help the profits of companies
  • Detects fraud
    • Helps better decision making
  • Better customer reach and service

Key areas of interest

  • Big data analytics reduces cost usage. Cloud-based analytics also help organizations store data and improve business efficiency.
  • Faster and better business decisions can be made as businesses can immediately analyze the data that is generated through IoT
  • New products can be marketed and developed because data analytics help organizations understand their customers better. Developing new products based on customer needs and preferences.
    • Big Data, also helps organizations identify and target risks by observing the patterns. In addition, Strategies are developed to eliminate and minimize the risks

Importance of Big Data Analytics

Learn more about Big Data Analytics and get certification from the best.

Henry Harvin Big Data Analytics Course

Renowned award-winning Ed-tech company trains professionals in various career-building courses.

Big Data Certification Course is a specialization course in Advanced Big Data techniques. In addition, vetted by experts this course is integrated to help students understand the subject. You can master both knowledge and skills in this course. Also,get hands-on experience in projects and be trained in the unique GCAO pedagogy.

Get trained in tools and technologies like

  • Hadoop
  • Spark
  • HDFs
  • YARN
  • MapReduce
  • Hive
  • Machine Learning
  • Advanced text analytics
  • Predictive Analytics
  • Data Mining
  • Statistics
  • Natural language processing

 The Big Data Analytics course has many benefits. It has 9 courses in 1 course. Therefore this is a huge advantage to candidates, as they get to benefit the most. The course includes training, certification, and projects. Also, placement, internship, E-learning, Bootcamps, and Hackathons are part of the course. Included in this course is a Gold Membership of Analytics Academy for 1 year.

Skills Covered in this course

  • Memory Tuning
  • Data Broadcasting
  • Cluster Management
  • Data Locality
  • Data Analysis
  • Dynamic Resource Allocation

Get trained for 32 hours . Also, online, live interactive sessions are available in this course. Get trained in projects in related fields like Kafka and Spark etc.

Hallmark CBDA Certification from Henry Harvin recognized by the government of India. Also, get access to E-learning. The course also includes videos, content, assessment, tools, and techniques. Experienced trainers with over 15 years of expertise in the industry. Guaranteed job placement and internship.

Please check out the other courses by Henry Harvin

Henry Harvin Data Science and Academy

  • Business Analytics with R(CBAP) Course
  • Marketing Analytics with R(CMAP) Course
  • Financial Analytics with R (CFAP) Course
  • Business Analytics with Python(CPBA) Course
  • Marketing Analytics with Python(CPMA) Course
  • Financial Analytics with Python(CPFA) Course
  • Tableau Course
  • Power BI

And More. 

Visit the website for more information about Data Science and Analytics Courses.

Contact: 91 9891953953 for more details.

How is Big Data Analytics Useful

Amazon, Facebook, Netflix  Instagram, and other corporate businesses use big data analytics to discover useful information about their customers. The applications of Big Data analytics are numerous. Big Data Analytics helps in making better business decisions based on predictions. Companies that use big data analysis have performed better than companies that do not. Big Data also identifies individual consumer preferences and recommends better options to them. On the whole, companies are quick and timely in decision-making. Facebook, marketing agencies, study and research the result of their campaigns, promotions, and advertisements. This helps their business make good profits. Finally, it contributes to better and more advanced consumer and customer experience. The companies also make better profits

 E-Commerce and Big Data Analytics

Data analytics allows e-commerce companies to analyze the data they have implemented while using their platforms. E-commerce uses this information to target the customers with products and services of their choice. It helps in overall customer engagement, better shopping experience, and sales. Example: Amazon

 Role of Big Data Analytics in the Entertainment Industry

  •  Entertainment companies develop promotional products to get customers’ attention.
  • Better content creation is produced.
  • The choice of content that is popular is understood and strategies are made to retain the customers.
  • Content recommendations are also made with the help of data analytics
  • Data also helps them to identify popular content and produce the same genre of content. Examples: Netflix, and Spotify.

Big Data Analytics in Business

Businesses can communicate with their customers through emails, text messages, WhatsApp chats, etc. Mass messages in the form of emails or texts, can be sent at once. Target their customers with their preferences and rewards. The hospitality and tourism industry aims at better pricing, and adjusts pricing during the peak season and off-season. Examples:  Swiggy, Ola, Uber, Travel, and Tourism industry

Role of Big Data Analytics in Health care Industry

  • Manages a huge number of patient records
    • Tracks Insurance details
  • Prescription details
  • Bills and financial matters
  • Hospital Administration
  • Makes decisions that are life-saving

Role of Big Data Analytics in Education

Educational institutes use analytics to plan a suitable curriculum and monitor students’ progress and assessments. Ed Tech Companies have a larger outreach with data analytics.

 A Woman Making a Business Presentation Stock Photo

 Types Of Big Data Analytics and their functions

Data can be divided into 4 types. These types of analytics allow businesses get a clear view of the data and reach their customers. Each type of data analysis helps the organization in creating a strategy for better performance.

  • Descriptive
  • Diagnostic
  • Predictive 
  • Prescriptive.

Listed below are key types of analytics and the role they perform.

Descriptive Analytics

This is the first step in understanding this raw data. It is basically, the use of current and historical data to study patterns, trends, and correlations. Descriptive analytics is the most basic type of data. Most of the organizations use this analysis to perform tasks. It helps in identifying trends in current and historical data and other changes This promotes better decision-making. Companies use this data to understand what has happened to date. For example, Netflix uses descriptive analytics to see what programs and genres interest their subscribers. This information is also used to develop their content creation.

Diagnostic Analytics

Is a  type of big data analytics that investigates and answers the question Why? It provides a diagnosis of a problem. Therefore, you understand the reasons why a certain thing has happened. This technology investigates the cause of the problem or an event. Diagnostic analytics is used by businesses to understand why there is a pattern or trend. It analyses customer preferences among other things. Companies use these analytics to detect fraud or to point out why the company is going through loss. Moreover, It also helps to identify technical problems and study traffic increases on websites. HR, Pharmaceutical companies, and hospitals use diagnostic analytics for all their tasks.

Predictive Analytics

Helps predict or forecast the outcomes of decisions, It also predicts future events and trends. It gives us an idea about what might happen in the future. The predictions could be in the near future or far away. It gives a forecast of situations, so as to help companies make better strategic decisions. Entertainment, hospitality industry, and Markets use this to predict future trends, so they can prepare for it ahead of time. Campaigns are run based on forecasts. Prevention of malfunction in manufacturing machines is another benefit of predictive analytics.

Prescriptive Analytics

Data is used to decide on the best way or method of action for a problem. It gives recommendations regarding what steps have to be taken to make businesses profitable. Companies study large data more efficiently with machine learning algorithms. It also gives solutions based on the requirements of companies. For example, social media, dating apps, banking, and investment ventures all depend on prescriptive analytics.

The businessman in big data management concept stock photography

Tools used in Big Data Analytics

There is no one special technology that supports big data analytics. It is a combination of several technologies. The technologies work together to bring the best out of the information created.  Data Tools are software that help in segregating and uncovering data to use in various applications. . Different tools perform different tasks.

Listed below are popular big data tools.

Hadoop (High Availability Distributed object Oriented Programme

  All tech giants use Hadoop because it’s the best tool. It efficiently stores and processes large amounts of data. It distributes large data into smaller segments. Easily implemented as it is very flexible

Apache Cassandra

It is an open-source distributed database management system. Therefore it can handle big data such as structured, Unstructured, and Semi-structured data. Facebook first developed this tool. All major companies use this tool to handle data.

Apache Kafka, 

It is a distributed event streaming platform that is open source. Companies use it for critical applications, streaming analytics, and data integration.

Apache Spark 

It is a data processing framework. It performs tasks on large sets of data . And it is open-source analytics for large-scale data processing and programming.

MongoDB

Is an open-source, cross-platform document database written in C++ It can store or retrieve information. And it develops internet applications.

Tableau

The best software and visualization tool that transforms data into meaningful insights. Delivers speedy analysis with the help of dashboards and worksheets. It works better with Hadoop

Hive

Works with the help of Hadoop. Can work with petabytes of data. It is Open source platform that can help in the storage and processing of large data using SQL

R-Programming

 Domain-specific language Helps data scientists make statistical analysis, and scientific computing

Future Trends In Big Data Analytics

The future of big data is bright and exciting. It is important to know the future trends in big data, so you take advantage of these trends. Future trending areas in big data analytics.

  • Analyze data on the cloud
  • Focus on Actionable data
  • Predictive analytics will gain dominance in the future.
  • Renewed healthcare by clinical analytics
  • AI and Machine learning will continue to play a vital role
  • IoT (Internet of things) will push streaming analytics
  • Cyber security will gain importance
  • Data as Service
  • Quantum computing
  • Natural Language processing
  • Edge computing
  • Hybrid clouds
  • Dark Data
  • Smarter AI

Careers in Big Data Analytics

 Yes, data analytics is a great job. There will be no looking back or regrets if you choose a career in Big Data Analytics. You can have an amazing career in this field not only in India but anywhere in the world. Data Scientists are in great demand. The requirement for data scientists has increased a hundredfold during these past 5 years. Therefore, this is perhaps the best time to take advantage of the situation and join a Big Data Analytics Course. 

Companies all over the world give priority to data analytics. And there are many job openings all over the world. However, very few people have this skill. This requirement for this field will continue to boom in the coming years.

Big Data has opportunities for all professionals in various industries and different sectors, There are many opportunities for you to take up a career in reputed brands. However, you need to take some steps before you enter this career. Get good practical experience To enter this field. Enroll in an advanced course plan taught by reputed institutes.  

Listed Below are the top Careers

  • Data Base Administrator
  • Big Data Engineer
  • Data Scientist
  • Big Data Architect
  • Data Base Manager
  • Modeler database
  • Data Base Developer
  • Data Base  Manager
  • Security Analyst
  • Business Intelligence Analyst

Switching Careers to Big Data

Are you wondering whether you can change your career to Data Analytics? Then the good news is YES! You can.  Do not get boxed in your present position. Take a leap of faith and action to follow your dream. The world needs skilled trained and certified data scientists. You can be one of them. Great career opportunities and high salaries are part of this job. It doesn’t matter what your background is. The skills you have acquired in your previous work will surely be an added advantage. Focus on the skills required to make a career in Data Science Analytics. Enroll in an advanced program. A program that gives practical attention to hands-on learning. Get hands-on experience with tools and techniques. And you are ready to go into another exciting, challenging, and ever-evolving field.

Conclusion

The scope of big data analytics is vast and exciting. Moreover, it is a continuously evolving field. As new technologies are introduced frequently. Therefore, advancement in big data analytics can be called a revolution looking at how it has changed the world. What it can become in the future is far more exciting. Research in this field is very promising. Future predictions will change the world we live in. This revolution will make living much easier and perhaps make it more thrilling. Plan to make data analysis your career. It is one of the best jobs with high salaries in the market. It’s time to catch up with the best!

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FAQ’s

 

Q1. Is Big Data Analytics difficult and complex?

Ans. Big Data skills like Python, SQL, R, and statistical analysis can be challenging. If you plan well and continue your efforts, you will find it easy to overcome this challenge. The process is hard, but the end is very rewarding.

Q2. Is Big Data used in E-commerce Industry?

Ans. Yes, E-Commerce uses big data to personalize the customer’s shopping experience. It increases sales. Improves customer engagement among other uses.

Q3. What are the top tools to learn in Big Data Analytics?

Ans. Learn Hadoop, MongoDB, R, Python, Tableau, PowerBI, and Apache Spark as they are top tools. These are the top tools in data analytics.

Q4. Are there careers abroad after completing the Big Data Analytics course?

Ans. The number of jobs in data analytics has risen by nearly 50%. all over the world. The salaries for data science professionals are very high. This is the best career to choose. There are numerous career options abroad after this course. Some training institutes can also help with placements in India and abroad after this course.

Q5. What is the difference between Data science and Data Analytics?

Ans. Data Science is a broad topic that studies large data sets. Whereas, Data Analytics is a more focused and application-based study. 

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