Imagine going through voluminous sets of raw data for days together just to come up with a simple one-line conclusion. Sounds like a nightmare? While the conclusion might look simple, the process of manually analyzing raw data isn’t easy at all. However, Data Science and Data Analytics do the tricks here, which is why they are one of the most sought-after skills today. Want to upskill yourself in Data Science with a professional certification from IBM Data Analytics Course? Read further to know everything in detail about the IBM Data Analytics Course.
What is Data Analytics?
Data Analytics is a branch of Data Science that deals with analyzing and interpreting raw data into useful facts and figures that help in decision-making. To simplify this further, Data Analysis is a part of everyday life. Every small decision we make is based on various aspects like past incidents, current scenarios, our personal choices, etc.
For Example, you choose a restaurant for dinner based on various criteria such as ambiance, cuisine, the time needed to travel, etc. Similarly, various kinds of Data and Data Analytics are used at multiple levels to help run an organization, business, or government.
Why is Data Analytics Important?
Data Analytics helps an organization understand the environment they are in – in terms of employees, customers, government, etc. It facilitates organizations to tackle problems efficiently and come up with viable and beneficial solutions. Data Analytics is broken into 4 kinds to answer different kinds of questions in dealing with a critical situation – Descriptive, Diagnostic, Predictive, and Prescriptive. Take an example of a problem statement to understand these better:
“Children’s increased addiction to electronic devices”
Descriptive Analysis of Data: This helps in understanding the problem statement thoroughly. It talks about what the current situation is in comparison to what it used to be. Understanding the problem in detail is the basis on which solutions are derived. Hence, this kind of data analysis can be considered the first step in problem-solving.
In the case of our example, Descriptive Analysis of Data will revolve around the number of children considered for analysis, age group, location (Rural/Urban), average time spent on electronic devices per child, family background, etc.
Diagnostic Analysis of Data: This helps in understanding the cause of the problem statement i.e., why something has happened. Based on facts gathered under descriptive data, a relationship is established between each factor and the problem statement.
In the above example, Diagnostic Data Analysis helps in understanding why children are addicted to electronic devices and why the addiction has been increasing constantly. One of the reasons could be that both parents of the child are working and aren’t able to effectively monitor the child.
While Descriptive Analysis talks about the family background, Diagnostic Analysis talks about why family background has an impact on the child’s behavior. Understanding the cause of a problem is half the problem solved.
Predictive Analysis of Data: This kind of analysis gives an insight into what can happen in the future. Understanding how a problem can affect in the long run will help in determining the criticality and immediate actions that have to be taken to ensure things are in control. Predictive Analysis, in our example, will help in ascertaining how addiction to electronic devices will affect children’s behavior when they are adults.
Prescriptive Analysis of Data: As the name suggests, this analysis prescribes necessary precautions and corrective measures to tackle problems efficiently and ensure losses are minimized. In the example above, the prescriptive analysis will help in coming up with measures to reduce addiction to electronic devices such as increasing parental control of devices, educating children and parents about the pros and cons of electronic devices, etc.
Steps Involved in Data Analysis
- Understand the problem – This step deals with deciding the problem statement and collecting all facts and figures around it. The problem can either be to tackle a pain point or start a new line of business or improve the current line of business but the end goal is to increase efficiency and maximize profits.
- Data Collection – Data collection revolves around collecting raw facts from various sources. Surveying is a popular way of data collection. This data acts as the basis for further analysis.
- Data Cleaning – This process involves the cleaning or removal of unwanted or redundant data. Raw data is generally not organized and hence, it will require a thorough check to understand its relevance. Sometimes, secondary data collected may not be relevant at all. Cleaning of data will reduce data size, increasing the speed and ease of data analysis.
- Data Exploration and Analysis – Raw data by itself will not add any value. Hence, various data analytics tools are applied to raw data to come up with meaningful results.
- Interpretation – The final step of data analysis is to interpret the results of the analysis. A connection is made between the analyzed data and the problem statement and is published in a manner that is understandable to those who need this data set for decision-making.
Scope of Data Analytics
There is a steady increase in the importance of Data Analytics today since its techniques are proven to be effective in almost every sector. As stated earlier, Data Science is one of the most demanded skills in the market today with lucrative job opportunities.
Based on a report published by Acumen Research and Consulting, the global market size of Data Analytics is expected to grow to USD 330 billion (Approx.) in 2030 from USD 31 billion (Approx.) in 2021.
Here are some ways different industries use Data Analytics to increase their business:
- Media – A show’s success or failure majorly depends on its audience’s taste. Data Analytics in media helps in analyzing the location, gender, age group, tastes, and preferences of its audience, which will then aid in creating content that will suit the requirement of its audience.
- Education – The education system can use data analytics to understand where the students stand in terms of their knowledge. This will help teachers improve or change their teaching strategies and methods to facilitate students learning faster and
- Government – Data Analytics is used immensely in government sectors as it helps in understanding the current situation of the country from various angles such as poverty, employment rate, death and birth rate, literacy rate, etc.,
Data Analytics act as strong evidence for all policies and laws laid by the government. It also supports the government in planning better to cater to the needs of its citizens.
- Manufacturing, Retail, and Wholesale – While the manufacturing sector uses data analytics to understand the needs and tastes of its customers and create products accordingly, retailers and wholesalers use data analytics to understand customers better to give them a customized experience, offer discounts and attractive sales, thereby benefitting their business along with increasing customer satisfaction.
- Banking – Similar to the retail industry, Banking Industry uses Data Analytics to understand customers’ requirements and customize plans accordingly to offer value-driven services.
Tools Used in Data Analytics
Some of the popular tools that are used in analyzing data are Python, R, Tableau, Power BI, QlikView, Apache Spark, SAS, etc.
Data Analytics Courses
Based on an article published in Education times in December, Data Analysts are considered as indispensable parts of any organization. As per the report, 45% of the overall increase in jobs in India was due to data analytics requirements. With a booming and competitive career, every aspiring data analyst should be thoroughly skilled to meet the employer’s expectations.
There are various courses that equip students with knowledge of Data Science and IBM Data Analytics Course is one such. IBM Data Analytics Course is one of the best certifications available for all Data Analyst Aspirants.
IBM Data Analytics Course
IBM – International Business Machines Corporation is a multinational tech firm with close to 300,000 employees (Approx.) globally. It is prominently known for the production and sales of computer software and hardware along with cloud computing and data analytics.
With an annual revenue of $60.53 billion in 2022, IBM is undoubtedly one of the tech giants in the world. IBM Data Analytics Course is a self-paced course designed and taught by employees of IBM having in-depth knowledge of the field of Data Science.
IBM Data Analytics Course Structure
The link to this course “IBM Data Analyst Professional Certificate” on IBM’s official website directs you to Coursera, however, there are other online institutes like edX and Simplilearn offering the same course with IBM certification as well. IBM Data Analytics Course has 8 modules, all of which have to be completed in order to be eligible for the certificate.
- Module 1: Introduction to Data Analytics
The first module of this course gives an insight into the world of Data Analytics. Starting from who a data analyst is and the difference between Data Analysts, Data scientists, and engineers, you will understand the scope of a data analyst. You will also be given exposure to data ecosystems, databases, and data lakes.
You will understand the career opportunities and career progression prospects of senior industry leaders. Towards the end of this, you will know the fundamental analysis of data, communicating end results, and use of visual tools like dashboards.
- Module 2: Excel basics for Data Analytics
Excel is one of the essential tools for working with data. This course will help you understand excel thoroughly along with its advanced functions such as VLOOKUP, pivot tables, etc., which will help in analyzing data. This module is helpful for those who aren’t interested in data analytics too.
- Module 3: Data Visualisation and Dashboards with Excel and Cognos
Visuals and picture representations give a bird’s eye view of the data analyzed. Similar to line, pie, and bar charts, you will learn advanced visualization tools like Treemaps, Scatter Charts, and Histograms. Cognos Analytics is a business intelligence tool that helps in creating dashboards with interactions, which will also be covered in this module.
- Module 4: Python for Data Science, AI & Development
Python is a programming language and the demand for individuals with knowledge of python is always high. Without any prior experience, this course is sufficient for you to understand in detail the concepts of python and become a programmer.
- Module 5: Python Project for Data Science
This module deals with the application of techniques learned in the previous module on real-world scenarios.
- Module 6: Databases & SQL for Data Science with Python
SQL knowledge is a compulsory requirement for analysts and scientists who deal with data. Large volumes of data are stored in databases and are extracted using SQL. This module helps in creating SQL queries to extract the right set of data.
- Module 7: Data Analysis with Python
As discussed earlier, Python is a programming language to deal with data sets. This module helps with the analysis and creation of data models using Python.
- Module 8: Data Visualisation with Python
This module helps you learn in detail about all advanced tools for visualizations and the creation of dashboards.
- IBM Data Analyst Capstone Project
This is a real-world project which will give you hands-on experience in Data Analytics. You will apply all tools and techniques learned in the other modules to complete this project. This project is a great add-on to your portfolio and is a good opportunity to showcase your data analytical skills. Upon completion of all the above modules along with the project, you will be entitled to receive your professional certificate.
Why IBM Data Analytics Course?
IBM Data Analytics Course is a self-paced, in-depth course that will transform you into an efficient data analyst in a short span. This course awards you with a professional certificate which means that it is intended to get students job ready with hands-on projects and career support.
Certain modules in this course have hiring partners which will help you kick start your data analyst career right after completion of this course. The course is also widely recognized in the industry and gives you the authority to publish the certificate on networking sites like LinkedIn.
Faculty of IBM Data Analytics Course
The faculty for this course comprises 9 people out of which 5 are from IBM. Each of them with vast experience in the field of data science adds largely to the popularity and demand of this course.
Career Prospects and Salary for Data Analysts
You begin your career as a data analyst or a junior data analyst. As you gain experience, you move into the role of a specialist i.e., financial analyst, business analyst, etc.., You can then choose to grow in the same line and become a team leader/manager or decide to be a data scientist.
You can also choose to be a freelancer if you prefer your work to be flexible in nature. Upon gaining the required experience, companies hire you to work as a Data Analytics consultant for them. The average salary of a fresh data analyst in India is ₹ 4.3 lakhs (Approx.) Data Analyst jobs are considered one of the most rewarding careers in terms of salaries, as you grow up the ladder.
- Online Data Analytics Courses
- Data Analytics Course in Gurgaon
- Data Analytics Course in Noida
- Data Analytics Course in Ahmedabad
- Data Analytics Course in Bhopal
- Data Analytics Course in Chandigarh
Top Companies hiring Data Analysts
Data Analysts may be called by different titles but they are required in every organization. Some of the many companies hiring Data Analysts are:
- Tata Consultancy Services
- Cognizant Technology Solutions
- S&P Global
Institutes Offering Data Analytics Courses Aligned With IBM along with Fee Details
As mentioned earlier, IBM on its official website has the Data Analytics course with Coursera. However, there are other online platforms like Simplilearn and edX offering the same course with certifications from IBM.
Coursera offers a free trial for 7 days. You can avail of the course free of cost if you complete it in 7 days. However, the suggested time to complete this course is 4 months (Under 10 hours of study per week) and the subscription fee with Coursera is $39/month, which is $156 in total for 4 months (INR 13,000 Approx.) This course is rated 4.6/5 with over 11,800 reviews and 1.09 lakh enrollments.
This is a self-paced course too, that will take 12 months to complete with a few hours of learning on a daily basis. This course is ranked as the best data analytics course by Career Karma. Course Fee: INR 54,000 (incl. tax). EMI Options are available too. This course is rated between 4.5 to 5/5 stars with over 61,500 ratings.
This is a self-paced course that will take 10 months to complete with 2-4 hours of reading per week. This course is priced at INR 64,861.
1. Who can enroll in the IBM Data Analytics Course? What are the eligibility criteria?
If dealing with numbers and large amounts of data interests you, this course is for you. There are no specific eligibility criteria required for the course. However, a basic understanding of computers and knowledge of school-level mathematics is essential.
2. Is there any age restriction for the IBM Data analytics course?
There is no age restriction to enroll in this course.
3. Are there any discounts for the course offered by Coursera?
There is a free trial for 7 days. There is also an option to ask for financial aid if you need help in paying the course fee.
4. Does the IBM Data Analytics course have in-person classes?
The course is fully online and does not require you to be present in person.
5. Does IBM offer jobs right after completion of this course?
No, IBM doesn’t offer guaranteed jobs after this course. However, each module has a list of hiring partners and you can apply accordingly to start your data analysis career with them.
6. Does the certification of the IBM Data analytics course have industry-wide recognition?
Yes, this course is formulated keeping in mind the skills required for a data analyst in the industry. It is designed by experienced people in this field and the certificate is widely accepted by various multinational tech firms.
7. What are the risks and complexities of Data Analytics?
The basis of data analysis is raw data that is acquired from various sources. Some of these sources may not have data that is fully genuine. This will lead to the wrong interpretation of data and may not help in making the right decisions. There is also a breach of privacy to customers’ information. Another complexity here is the cost of Data Analytical tools. However, being cautious and aware of the information and tools that are being used will help in mitigating these risks.
Data Analysis is a part of every organization – from a small start-up to a tech giant, every company relies on data of one kind or the other for running its daily activities, formulating its policies, coming up with plans and goals, meeting the needs of its customers and most importantly to run the business efficiently with minimum losses. Considering the importance of data today, Data Analytics is a skill that is needed by employees at all levels, irrespective of their academic background.
Data Analytics not only offers corporate jobs but is also one of the most popular freelancing careers in the present day. Acquiring the skill of Data analysis will help you have your own set of clients, and work flexibly at the convenience of your home and all of this is backed with rewarding monetary benefits.