Table of Contents
Why Big data analytics course?
The scope of big data analytics course will reach its peak in the coming years. However, Increasing demand and a short supply of skilled big data analysts will make way for a plethora of job opportunities.
whatever may be your background, whether it is science or commerce. Anyone can pursue a Big data analytics course (become a big data analyst), and make a career in this field. You can do this course after graduation and can become a big data analyst. Big data analytics is not only for IT professionals, even Non-IT professionals are also eligible for this role. Additionally, provided they have good knowledge of statistics and cutting-edge analytical skills. If you have a bachelor’s or master’s degree in subjects mathematics, statistics, economics, analytics, computer science, and data science then that is an added advantage.
Companies can make faster and better decisions using data analytics. It reduces overall business costs and develops new and innovative products and services.
What is Big Data Analytics?
Numerous sources create data at a very high speed. We use social media applications every day. For ex:- Facebook forms data of more than 500 terabytes every single day, take the video-sharing platform youtube, which has about two billion users and creates a huge amount of data daily. we can use this data in a meaningful way. This is where big data analytics comes into action.
Big data analytics is the process of collecting, processing, analyzing, and extracting meaningful information from the data. Big data analytics is a set of techniques and technologies that needs new ways of integration to reveal large hidden values from the huge amounts of data. This data is more complex and is on a large scale. It mainly focuses on solving problems in better and more productive ways. Hence, after getting certification for the Big data analytics course from a reputed institute, you can easily get into a well-established company as a Big data analyst.
Different activities generate information/data. Hence, doing analytics of that data and making meaningful insight of this data helps decision makers/companies to take the better and right decision. So, this is the main benefit for the companies and government to focus on the right areas based on that data.
Scope of Big data analytics courses
With the increase in competition, it has become necessary to find the best technology that suits your needs and make sure, you get the best training. Furthermore, a Big data analytics course will fast-track the growth in your career. Hence, the candidates should make sure to pursue this course from reputed institutes.
Big data analytics has become an important part of many companies, even the companies that do not have any relation to technology. Data analytics has become vital in every field. Companies are flourishing in their domain by using data analytics.
1. High demand for big data analysts
Every organization is implementing big data analytics to overcome cutting-edge competition. With this, the demand for big data analysts is also increasing. With proper training and certification in a big data analytics course from a reputed institute, there is a manifold increase in the chances of getting the right job.
2. Faster career growth
Organizations are also facilitating advanced training on Big data analytics to meet their requirements. However, most organizations are facing the biggest challenge which is attrition of employees. This means, they are not able to retain the employees after they gain the skills in Big data analytics. This directly indicates the demand as well as the opportunities for faster carrier growth. So, if you want to fast-track your carrier, it is advisable to understand the scope of the Big data analytics course. And, further, gain the skills related to Big data analytics.
3. Increased financial benefits
The salary of the person depends on many factors. Some of the factors which play a major role are your credentials, your certification, experience gained, the location, industries, and services that you worked in. Depending on the skills, knowledge and expertise in the field of big data analytics, you can get high financial benefits. Also, as you gain more experience and go to a higher position, your remuneration will also increase.
4. Learning opportunities
If you are planning to learn Big data analytics skills, the opportunities are plenty. Many Private Institutes, Training institutes, and Online channels, like youtube, Social media, and Government organizations are facilitating reasonably good material for learning the skills. Also, some of the IITs are arranging the online course as well as conducting exams and providing certifications.
5. Overseas Opportunities
Across the globe, the demand for Big data analytics is growing by double-digits. The availability of the resource in their countries is very low, which is visible in many of the Job portals. Hence, for whoever understood the scope of the Big data analytics course and mastered the skills, overseas opportunities are knocking at their door.
Depending on the skills gained from big data analytics courses, the opportunities in various organizations could vary, but in general, the roles and responsibilities of a big data analyst will almost remain the same.
Roles and responsibilities of a big data analyst
- As a first step, the information (data) is collected from different sources and stored in the database
- Then extract the data from the database according to your requirement
- Since the data is in the raw format, so your task will be to clean the data, like dealing with the missing information and removing unwanted data.
- Analyzing the data
- Draw insights from the data. Design-build test and maintain backend code.
- Since you are doing this for a company or any client, so you have to create visualizations and dashboards
- Make people or your team members understand the result
The scope of the big data analytics course will help you to gain an understanding of the above roles and responsibilities. Above are a few examples of what a data analyst will be doing in a given role.
Hard and soft skills required by a big data analyst
some of the important hard and soft skills that you need to become a data analyst are,
1. Technical skill
- A basic to an advanced level of excel understanding is minimum.
- You should know about the databases and programming skills like SQL
- You should have some Mathematical and Statistical ability
- Working knowledge of different programming languages, like Python, R, and Statistical Analysis System(SAS) is also required. Python is a basic language, but depending on company requirements you should also be aware of R and SAS
- You should have a good understanding of data visualization tools like Tableau and Power Business Intelligence(BI) for handling huge amounts of data
2. Analytical skills
you also need an analytical mindset. Data Analytics is about answering questions and solving business challenges that require some keen problems solving skills.
- Critical thinking: No matter how complex the task is, your main objective is to critically think about the solution, in this way you will be able to help the company take better decisions
- Research: Identifying the sources of data, the accuracy of the results depends on how much the data is well researched.
- Data analysis: The data which is provided will be in huge quantity, from this data you have to draw insights, interpret the data and help the organization in taking better decisions.
3. Soft skills
- You also need excellent communication skills like verbal, visual, and written skills, so that you can share the insights clearly with the client
- Other than this, you should also have leadership skills, adaptability, and good teamwork.
You can get all the above skills by enrolling in the big data analytics course with Henry Harvin.
Scope of big analytics data course in various domains
The scope of the big data analytics courses is increasing and spreading to various fields. By completing the course, all the above-discussed skills are mastered. These skills can be applied in the following domains like
Marketing analysis details are used to recommend the existing organization to enter a new market or exiting from the current market. For example, Vedanta entered into semiconductor manufacturing, Adani Group entered to Telecom sector, and Citi Bank exited the Indian Banking system. Additionally, these analytics predict customer Intelligence, Customer retention, and customer churning for better growth.
The demand and supply forecasting is predicted using historical data in the supply chain functions of the organizations. Business Process Analytics, HR Analytics, Airlines launching new routes between the cities based on Big Data Analytics, etc
3. Use of Data Analytics by Government
Data analytics is used to identify Fraud detection in different departments. Few of the examples are given below.
- Terrorism detection
- Identification of people who avoid paying tax. Also, in
- proper implementation of government schemes(Cost reduction)
- Social security scheme formulation
- political election strategies to win the elections
4. Risk Management by different organizations
Financial institutes are formulating the Credit risk models, Market risk Models, Fraud detection Models, Insurance claims, profitability, etc based on Big Data Analytics.
5. Web and Social media Analytics
Many social media websites are at the forefront of using Big data Analytics to predict customer interest. However, digital marketing organizations are using these analytics for converting advertisements into sales.
Additionally, Other than the above domains, many of the important sectors use Big Data Analytics to predict core parameters in their field. Few of the sectors are listed below.
- Health sectors
- Oil and Gas Sectors
- Agricultural sectors
- defense sectors
- aerospace industry
- manufacturing sectors
It is also helping in automation as well as in research to improve service and productivity.
All the above-discussed industrial sectors (domains) are using various analysis techniques that are given below
Types of Big Data Analytics
These are also called levels of data analytics. While there are many analytics methods and techniques for analyzing data. Below specified four methods are applied to any data to derive insights. The scope of the big data analytics course will help you to gain knowledge of the below types
1. Descriptive analytics
This is all about “what happened”. This provides insights into past events. The primary intent is to find insights by using the statistics that describe the data. Based on this data analysis, the reports will be generated on revenue, profits, and sales of a company. The tools used for descriptive analysis are metrics and statistics. These data analytics are used to understand historical trends.
2. Diagnostic Analytics
This is all about ”why did it happen”. This will take the insights from descriptive analytics to dig deeper to find the source of the problem. Examples- drilled down data mining, and data recovery. The tools used are Package configuration descriptor(PCD) and regression analysis.
3. Predictive Analytics
This is all about “what will happen next”. This leverages historical data and trends to predict future outcomes. The techniques used are machine learning algorithms. Example:- Future sales and revenue generation of the organization are predicted based on the historical and current sales, and revenue.
4. Prescriptive analytics
Prescriptive analytics is all about “what should be done”. This analyzes past decisions and events to estimate the likelihood of a different outcome. The tools used are neural networks and recommender systems.
The initial stages(data collection– SQL tool) for all the above analytics almost remain the same, whereas the middle(identifying the insights – Python) and later stages(outcomes or conclusions – Python and R) of the analysis have different tools, hence the candidates planning to pursue specific analysis technique has to undergo the relevant skill training.
Scope of big data analytics course in various job roles
It is no more a secret today, that the key to a successful business is data-driven decision-making. Data lies at the heart of the decision-making process of all organizations today and that has prompted the evolution of data-based job roles such as
1. Data Analyst
Data analysts have been around for ages, making this job title probably the most common and frequently occurring of the three.
- They draw insights and answer questions with data, they use SQL and scripting skills to extract and wrangle data, and their analytics and statistics skills to understand what the data is trying to tell them
- they use their storytelling skills to present their findings in a way that’s meaningful for the end consumer of the problems that they are solving.
- Data analysts are everywhere. They can work in business contexts or research contexts and pretty much in any industry and companies of all shapes and sizes
- the background of a data analyst tends to vary a lot, traditionally a data analyst would be someone with a bachelor’s or master’s degree in any area like math or computer science but the modern data analyst can also have a background that is related to business.
2. Data scientist
- The data scientist will be anywhere along the spectrum between data analyst and data engineer
- The data scientist will be sharing space with both data analyst and data engineer, but with an extra language like machine learning
- Unlike data analysts, data scientists also extract, wrangle, and draw conclusions from data, but they also work with machine language modules but they don’t go in-depth with that
- Data scientists are expected to have a very good understanding of machine learning programs and apply advanced methods, and use fewer out-of-the-box tools
- They will be doing some research in machine learning and building models from scratch
3. Data Engineer
- It is one of the well-defined roles of the three. They are more consistent. A data engineer may be a software engineer also
- Data engineers will be focussing on building and maintaining data infrastructure and data systems
- They set up data warehouses, data pipelines, and databases that the data analysts and data scientists use to access and work with the data
- They have strong computer science skills, they know all about databases, big data tools, and a variety of programming languages and frameworks.
Other than the three major job roles mentioned above, the Scope of big data analytics course will also have a variety of job titles which includes:
- Medical and health care analyst
- Market research analyst
- Business analyst
- Business intelligence analyst
- Operations research analyst
- Intelligence analyst
Companies hiring a big data analyst
As there are innumerable benefits of Big data analytics. The scope for big data analytics courses has skyrocketed. The job opportunities in this field have increased rapidly. Because data analytics techniques are being applied across the industrial sectors on large scale. Hence, Professionals who are working in this field have an impressive salary. 96% of the companies are planning to recruit new employees with appropriate skills to fill big data analytics-related roles in 2022. Rapid technology adaption across industries such as IT, Banking, Financial services, and insurance(BFSI). there is increased growth in demand for the roles of AI and machine learning in the year 2022.
The Indian financial market is expanding rapidly and is predicted to be the third largest market in the world by 2025. Across the world, many companies are recruiting big data analysts in different fields like healthcare, business, finance, pharmacies, and marketing.
Many of the world’s leading companies like Google, Intuit, Facebook, Apple, CISCO systems, IBM, TCS, Wipro, Infosys, Amazon, Flipkart, Intel, and Netflix are hiring Big data analysts. Apart from the above financial giants like the Big 4’s( KPMG, E&Y, PWC, Deloitte), Paypal and Barclays are also recruiting Big data analysts.
Characteristics of Big Data
The term big data refers to larger datasets(volume) that are more diversified which includes structured, semi-structured, and unstructured data(variety), and speed(velocity). These are the 5V’s
- Volume: it represents the amount of data generated, stored, and operated in the system. The increase in the amount of data generation and its storage will explain the rise in volume.
- Variety: it consists of various kinds of data, from tabular databases to images and audio data
- Velocity: the rate at which the data is generated is called its Velocity. Social media is generating the data continuously and adding to the data sets. constantly evolving data is used in the IoT devices.
- Veracity: Because of the complexity of Big Data, there will be some inconsistencies in the datasets. So, it will check the level of quality, accuracy, and uncertainty of data.
- Value: it is the value and potential derived from the data
Henry Harvin’s Big Data Analytics Course
This course covers the introduction to Big data. Big Data Analytics course provides an overview of Hadoop and Spark frameworks that provides prominent tools to handle a huge amount of data. This course will further advance the tools and technologies of big data ecosystems such as YARN, HDFS, MapReduce, Hive, and more.
9 in 1 course
- 32 hours of live and interactive online classes
- The internship provided to gain experience and knowledge on Big data analytics course
- The facility of projects in the related fields of Kafka, Spark, Big Data SQL, and many more
- Certified Big Data Analyst(CBDA) certification from Henry Harvin which is recognized by Govt of India and award-winning institute
- Guaranteed 100% placement post 1-year successful completion
- E-learning with video content, assessments, abundant tools and techniques for practice, and many more
- Regular boot camps for the next 12 months
- Free access to Hackathons and Contests
- Get 1 year Gold Membership of Henry Harvin
- Acquire good understanding about Hadoop Framework
- Work with Hadoop 2.x YARN and HDFS
- Gain immense knowledge of MapReduce
- Acquire knowledge about the basics of Hive illustration and loading various file formats
- Get hands on with external tables in Hive and pack data into Hive tables
- Operate Query Operations on Hive tables
- Understand about Apache Kafka as a distributed streaming platform
- Configure Spark and supervise performance modulation. Data serialization
- Become eligible for Big Data Analyst demanding posts
- Bridge the gap of thousands of high paid jobs in Big Data Analysts industries with shortage of talent
- Make structured and well planned choices for a Big Data Framework as an individual
- Express all functionalities of Big Data Analytics Framework in a Business model
- Make your profile unique from your peers during job interviews
- Get a Certified Big Data Analyst Certification which is rewarding
- Become an significant part of the company with Certified Big Data Analyst
- Professionally improve and develop your CV and Linkedin Profile
- Hadoop: Master your big data
- Hive: Big data SQL
- Spark: Stream and analyze the big data
- Apache kafka: A distributed streaming platform
- Advanced spark
- Complementary Module 1: Soft Skills Development
- Complementary Module 2: Resume Writing
Big data refers to the set of structured, semi-structured, and unstructured data. There is the production of high volume and velocity by the use of new techniques for personal or professional purposes. Big data analytics is the process of examining these data to decode hidden patterns, customer preferences, and other meaningful information to make the correct decisions. It is an emerging technology. any industries have adopted this technology. Hence, it has become a business industry on its own. However, As the demand is very high, the opportunities are also increasing. Also, increasing salaries in data Analytics may see professionals from other sectors switching careers and perfecting their skills in big data analytics. If you want to be a part of this new growth story, you can explore the big data analytics course by Henry Harvin.
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Ans. Gaining the knowledge and skills needed to become a big data analyst will approximately take around 10 weeks to 4 years. This range will also depend on the domain you want to enter and the efforts put in by you.
Ans. whatever may be your background, whether it is science or commerce. Anyone can pursue a Big data analytics course (become a big data analyst), and make a career in this field. It is always advisable to do a big data analytics course from any reputed institute like Henry Harvin.
Ans. The average salary package for entry-level big data analysts in India is Rs. 325,616. Depending on your experience, the salary may go up.
Ans. It again depends on different institutes, but the most common tools which are taught in the institutes are Hadoop: Master big data, Hive: Big Data SQL, Spark: Big data streaming and analysis, Apache Kafka distributed streaming platform, and Advanced Spark.
Ans. The demand for Big data analysts is increasing in different parts of the world. Especially Europe is one part where the demand for data analysts is very high. Furthermore, countries like the United States, Canada, Australia, and China also recruit candidates with good skills in Big data analytics.
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