Best Business Analytics Examples for Business Growth

Believe it or not, aspiring data analysis experts are searching for Business Analytics Examples. The main reason for their interest to get into business Analytics (BA) is the myriad of opportunities it creates. Any person with an intention to learn more about the course must educate themselves about the basics and important aspects of it. A lack of understanding about the scope for professional and personal growth can create confusion in the minds of potential employees. This is why a brief description and information related to the course are shared below.


List of best business analytics examples for business growth


What is and Why Business Analytics is Important?

An approach that involves the use of statistical models, data analysis, and related quantitative methods to resolve business problems is referred to as Business Analytics. A range of technologies and disciplines are derived from certain quantitative methods to assist businessmen in fixing problems in their businesses.

You can learn more with the explained Business Analytics Examples. Decision-making determines the success of an entity which is why regular consideration of an organization’s data using statistical analysis is carried out to help employers make and execute appropriate plans for business growth.

Data is an asset for companies solely dependent on information. They try to transform their data into an advantageous property which is why they are in constant search for possible solutions. Though business analytics is widely implemented in several organizations, its success rate is dependent on the skill set and knowledge of the hired analysts.

This is a fact because a lack of understanding of businesses and technologies will result in poor or no results for the entities. After all, commitment to continuous learning and identifying different solutions for fixing problems keeps the business going.


How is Business Analytics Classified?

Business analytics is subdivided into four categories based on their application and purpose. Here is a brief description of all.


●     Descriptive Analytics: This kind of business analytics deals with the extraction of data from various sources to share insights into history. In simple words, it will give you an opportunity to realize the impact of your past decisions. These insights can tell the decision maker if something is right or not but without proper evidence.

This is why it is used when combined with other types of BA. Data mining and aggregation are important procedures in descriptive analytics. It can assist the analyst to identify only underlying behavior and doesn’t help in making predictions.


●     Diagnostic Analytics: This sort of BA is utilized to find out reasons for the occurrence of an event in the past. It involves the implementation of techniques such as data discovery, drill-down, correlations, and data mining. You can get a glimpse of events and elements that led to a particular result. The analysis is done by the utilization of likelihoods, and probabilities, along with the distribution of results.


●     Predictive Analytics: Business analysts can predict future outcomes using predictive analysis. It is an important tool for forecasting because it considers discoveries of diagnostic and descriptive analysis to distinguish exceptional cases and groups and estimate future patterns.

Sentiment analysis is one primary application of predictive analysis. Opinions of online media users are collected to analyze and forecast the views on a particular topic as negative, positive, or neutral. Precise predictions can be obtained as the predictive analysis comprises validating and designing models.


●     Prescriptive Analysis: It is a statistical method with the scope to analyze a predefined game plan and recommend favorable outcomes. It will suggest a different course of action to drive a specific result if the existing plan is found to be an ineffective one. A strong feedback system is installed in this method to continuously learn and update the link between outcomes and actions.

Emerging tools and technologies are employed in the analysis method like Deep Learning, Artificial Intelligence algorithms, and Machine Learning. Internal and external data are taken into account to trigger favorable outcomes.


How Does Business Analytics Support Companies in Decision-making?

A number of foundational processes are involved in BA. Below are steps considered by an organization before choosing one method for data analysis.

●     Determination of the business goal

●     Selection of an analysis methodology

●     Collection of business data from a range of sources and systems.

●     Separation and integration of data into a data mart or a data warehouse.


Like any task, the process begins with smaller steps; A small sample of data is used for the initial analysis. Analytical tools are used for the same. Some employees use spreadsheets to have statistical functions. Whereas a few pick complex predictive modeling or data mining applications.

Relationships and patterns existing in the chosen data are identified. This step is then followed by raising questions to determine reasons for unmet business goals. This step will be repeated until the business goal is achieved.

Scoring, a statistical process, is used for the deployment of predictive models. The records from the available database are utilized for the effective action of chosen models. Decisions within the business processes and applications are made with the help of scores.

Business Analytics assists enterprises to make tactical decisions against unfortunate events. In most cases, automated artificial intelligence is employed to promote decision-making to assist real-time responses.


How is Business Analytics Applied in Organizations? – Best Business Analytics Examples

The stream of analysis has various purposes in different processes of a company. This is why many companies dwell on this method to achieve increased profits. Most organizations apply business analytics to sales, marketing strategies, predictive analysis, and financial efficiency. The application of this stream can be clearly understood with the help of Business Analytics Examples which is why a few illustrations are shared for your understanding.


●     Growing sales

●     Developing marketing strategies

●     Using predictive analysis

●     Improving financial efficiency

●     Increasing productivity


Growing sales: An online retail entity witnessed a decrease in its sales and identified that it was not able to level up despite a number of efforts. Then it used some of the tools of BA methodologies and incorporated them into a sales dashboard.

The application of business analytics shed a light on incompetent usage of data to drive sales. This led the retailer to make necessary changes in sales strategy based on the available data and enjoy an increase in sales by 24 percent.


Developing marketing strategies: An owner of a successful clothing store experienced a decline in customer purchases. He then installed a customized retail dashboard as per the demographic information about the target and current clients. The new action led to the identification of areas with strong sales numbers and scope for improvement.

The retailer differentiated the segment buyers based on relevant factors and tailored marketing strategies for each group. The dealer utilized internal data to interpret the purchase decisions of customers and grew his customer base.


Using predictive analysis: This is one of the best Business Analytics Examples to help you understand the impact of BA in a business. A gym team observed an increase in the cancellation of memberships. They implemented the predictive analysis method to find out the reasons for membership cancellations.

They utilized the historical data and added incentives to the membership fees to retain customers. The installed system sent alerts to the staff whenever it predicted cancellations as a reminder to share details about incentives and thereby increase the count of loyal customers.


Improving financial efficiency: One of the successfully running disease diagnostic brands witnessed a low percentage of collections, increased account receivables, and claim denials after a period. The company opted for Business Analytics the determination of possible causes for declining business.

The installed software used for intuitive online reporting helped the entity to use account-based metrics and increase engagement with the targeted audience and found out the reasons for excessive claim denials. Thanks to business analytics as it paved the way for fixing financial problems linked to denial claims.


Increasing productivity: A food company wanted to streamline commercial operations and boost its productivity. The entity availed the dashboard facility to help it identify its customer’s life cycles. This step facilitated the company to produce data to streamline marketing campaigns and sales activities which ultimately resulted in boosting its productivity.


Hope these Business Analytics Examples helped you link types of BA and their applications in the various industries.


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How Can an Individual Learn Business Analytics?

This is a brainer; several established institutes offer a range of online courses for the career upliftment of students. The course structure offered by an online company typically includes

●     Weekly online live masterclasses

●     Interactive doubt-clearing sessions

●     Exposure to real-life projects

●     Placement opportunity

●     Certification of completion


The duration of the business analytics crash course is usually 6 months when availed from an internet-based entity whereas a traditional institute will teach you the basics within 2 years. Institutes offering a 6-month course will also give you exposure to Business Analytics Examples which are nothing but real-life projects along with placement assistance.

Some students back off from availing of coaching due to the display of a high course fee on the college’s website. It is important for such budding analysts to understand that a few training institutes offer discounts to the majority of learners and let them benefit from them.

The fee structure varies from educational entity to entity. You can choose a program as per your career goals. Some prefer executive post-graduate programs, professional certificate programs, Master of science in business Analytics, global master certification in business Analytics, and Business analytics certification programs.


What is Covered Under Business Analyst Certification?

The syllabus includes a range of topics to assist the learner to become proficient in the subject. A seed of fear can get buried in the students’ minds on understanding the shared Business Analytics Examples.


But the delivery of assigned tasks to a fresh business analyst is easy as most institutes cover important required languages and methods in the syllabus; some of the commonly included areas are descriptive statistics, inferential statistics, estimation of hypothesis testing, Regression, playing with data, ANOVA, Component analysis and factor analysis, data mining, classification algorithm-decision trees, Classification algorithm-discriminant Analysis, Neural works, Linear and nonlinear regression, Model comparison and required improvement, Python for data science, Numpy libraries and array, and Pandas libraries and data frame.


Check here for the best Business Analytics Courses in Bangalore


What Are the Career Opportunities for People With a Business Analytics Degree?

As mentioned earlier, degree holders are keen on finding Business Analytics Examples to make the best career decision and learn about the scope of job vacancies. What makes an individual choose a professional field with no growth?

The only reason could be to waste money, time, and effort because a course with no market value is just trash. Business Analytics is that topic that will lay the foundation for human beings with big dreams. Below is a list of positions that serve as Business Analytics Examples for career prospects.


●     Business Analyst

●     Data Analyst

●     HR Analyst

●     Financial Analyst

●     Data scientist


Business Analyst:

An entity that is hired for the improvement of a company’s products, processes, systems, and services is a business analyst. They are required to find out areas with the scope for improvement and consider financially and technologically feasible options. Strong research faculties are essential to improve the weak spots.

They should coordinate with many departments which is why strong communication skills are mandatory. business analysts work in unison with financial and IT reporting teams. This role can be fruitful to those who aspire to work in different industries such as education, finance, E-commerce, agriculture, logistics, and banking.

A professional with expertise in business analytics can assist in the acquisition and retention of customers. You can refer to one of the above-explained Business Analytics Examples that speaks about predictive analysis for the retention of customers in a gym.

Companies hire business analysts and pay an annual average of 7.0 LPA. That being said, a fresher may begin their professional life with a package of 3.0 lakhs per annum and eventually gain experience to earn 15.0 lakhs per annum.

An individual with an experience of 1-2 years earns around INR 5.0 lakhs per annum while those with a minimum of 5 years of work experience can make INR 9.2 lakhs per annum. Senior business analysts in a company with more than 11 years of experience earn INR 12.4 lakhs per annum on average.


Data Analyst:

If you love conducting surveys to collect information, you are the right fit for this opportunity. A data analyst’s roles and responsibilities revolve around information related to certain topics. The professional will be responsible for the presentation of the data in a simple understandable manner.

The hired employees are directed to use technologies like SQL, Microsoft Access, Microsoft Excel, and other kinds of technologies. Reporting, data management, and statistical analysis for the effective completion of the assigned tasks.


A data analyst is expected to perform the below tasks as part of their responsibilities.

●     Collection of data

●     Analysis of data

●     Usage of statistical techniques and methods

●     Generation of reports

●     Identification of trends or patterns in the provided information

●     Database management


Having knowledge about SQL, data management, MATLAB, data cleaning, R, Python, data visualization, Linear Algebra, and Calculus can open doors for more career progress in the industry. All organizations rely on data analysis to attain success.

Employees allocated to deal with data are required to gather information from secondary or primary sources to promote a faster, more accurate, and more efficient decision-making process. You can relate this information to the ‘growing sales’ section mentioned under the category Business Analytics Examples.

A data analyst works with an average annual salary package of 4.3 LPA. The salary ranges from 1.8 lakhs per annum to 11.7 lakhs per annum. However, you must keep a fact in mind i.e., earning capacity of an individual varies from person to person based on their location, upskilling level, skill sets, experience, and other factors.

If you manage to complete a minimum of 4 years in a company as a data analyst, you can make a 5.3 LPA. On the other hand, homo sapiens with an experience of 7-8 years in data analysis enjoy an average salary package of 6 LPA. Similarly, professionals with more than 8 years of experience make more than 6 LPA.


HR Analyst:

Utilization of techniques and computer applications for the analysis of data linked to human resources is the job of an HR analyst. The presence of them in the organization is to present valuable information to the management post data collection, research, and analysis. Since the designation deals with human assets, the information provided by an HR analyst will assist the company in finding better candidates, motivating existing employees, and fixing problems related to staffing.


The key responsibilities of an HR analyst are:

●     Trend analysis

●     Statistical analysis

●     Attrition identification

●     Performance identification

●     Relationship management


The recruitment process can be improved with the involvement of HR analysts. Records from the hiring process are considered for making an effective strategy. This department of the workforce promotes employee training, upskilling, and experience.

An HR analyst is perceived to make an annual average of 4.7 LPA. The salary package ranges from 2.3 LPA to 8.3 LPA. This data is based on salary details shared by many professionals working in India. Also, it is crucial to note that your expertise, experience, zeal to learn and other factors determine your CTC.

An employee with less than a year’s experience can grab a package of 2.4 LPA to become an expert in the subject and enjoy a CTC of 7.0 LPA over a period of 8 years.


Also Read: Business Analytics Courses in Kolkata


Financial Analyst:

Profit is the main reason for the existence of any business. Financial analysts are individuals recruited for analyzing financials to increase the profit margin of a company. They deal with macroeconomic and microeconomic factors alongside studying the market trends, and demographics to make appropriate investments.

They must review the company’s allocation of investments and their purposes. Financial analysts devise plans to protect the organization’s wealth in unfavorable conditions and grow the same. You can gain a better understanding of this concept with the help of the above shared Business Analytics Examples that explain the improvement of the finance department in a diagnostic entity.


Better financial decisions can be made by the executive board based on the risks involved in their investment. The basic roles and responsibilities of an analyst handling financial data are

●     Predictions based on financial data analysis

●     Generation of reports

●     Identification of investment opportunities

●     Analysis of Profit/Loss

●     Financial planning

●     Suggestions on transactions

●     Portfolio management

●     Corporate Development


You can land a high-paying job if you possess the below skills

●     Financial skills

●     Analytical skills

●     Business evaluation

●     Financial modeling

●     MS Excel


The annual average salary of a financial analyst is 4.0 LPA. The average starting salary is 2.2 lakhs per annum whereas an experienced candidate may reach a CTC of 10.7 lakhs per annum. A financial analyst with a minimum experience of 4 years earns up to 4.8 LPA.


Supply Chain Analyst:

Enhancement of a supply chain through analysis is the work of a supply chain analyst. The employee must engage with other departments in the organization to learn about the effectiveness of the supply chain. For example, an ineffective warehousing system will be improved by the identification and rectification of faults in it.

An analyst dealing with information on the supply chain collects, and analyzes data, trends, and inventory, alongside managing operations. Most supply chain analysts have good quantitative analysis, decision-making, problem-solving, and critical analysis skills.

5.1 LPA is an annual average salary of a supply chain analyst in India. A newbie in the industry may receive an offer letter with a salary package of 2.4 LPA, while the ones with an experience of 9-10 years avail a CTC of 8.5 LPA. This also means the annual average pay scale for a supply chain analyst is higher than for a financial, data, and HR analyst.


Data scientist:

A human with an obligation to find valuable insights using the company’s data to help it in the amendment or creation of better plans for the achievement of success is a data scientist. They employ a range of scientific methods, algorithms, and processes to absorb insights from unstructured and structured data.

They use their tech skills, deep learning, and machine learning algorithms to filter the data and analyze it. Expert data scientists have skills like data wrangling, report generation, communication, data analysis, statistical analysis, programming, data visualization, and mathematics. Refer to the ‘developing marketing strategies’ subheading tagged under Business Analytics Examples for a simple explanation.

Believe it or not, a data scientist can tag a higher salary package compared to the above-mentioned positions. The annual average salary is 10.0 LPA. A typical Indian data scientist’s CTC ranges from 4.0 LPA to 25.3 LPA. A new entrant into the stream earns up to 8.5 lakhs per annum whereas an expert with a minimum of 7-8 years earns an average of 13.4 lakhs per annum.


FAQs About Business Analytics Examples


Who is eligible to apply for a business analytics course?

A graduate from any educational background can join the course. The instructors will teach the students the basics. Also, if you have an experience of 2 years or more in the relevant industry, you can learn the course at a faster pace and improve your career graph.


How to apply for admission to an institute?

You can find contact details of the institutes offering the certification for business analytics on their websites. You can use the application form to fill up the details and make the fee payment. Also, there are several colleges ready to brief you on the course when you have an in-person conversation with their faculty.


How can I clear my queries related to the course?

Many educational entities have a live chat option. You can utilize the same and seek answers to your questions from the customer care executives. If you are interested to have verbal communication, you can dial the number presented on your mobile screen and clear your confusion. The majority of the course-offering companies share a detailed description of the curriculum, fees, and benefits of availing admission through email. So you don’t have to worry about queries.


Who can benefit from the course, learning with business analytics examples?

Any person with a graduate degree from any discipline can learn skills, knowledge, and job with the help of the basic course in business analytics. People who choose an advanced course like business analytics for strategic decision-making can become C-suite executives, mid-to senior-level managers, analysts, and business leaders.

IIM SKILLS Data Analytics Course – A Detailed Review

Are you a student or a fresh graduate searching for IIM SKILLS Data Analytics Course Review? If yes, you have found the appropriate article that can help you gain the necessary information about the data analytics course offered at IIM SKILLS. This article will shed light on the course curriculum and benefits of becoming a student of a reputed training institute. This content also includes the basics of data analytics to refresh your memory. With no further waiting, start reading to make a better career decision. 

IIM SKILLS Data Analytics Course - A Detailed Review

Overview of Data Analytics

Data Analytics is the usage of tools and technologies to identify trends and patterns in the chosen data to help a company make better decisions to promote its growth. The employment of data analytics allows organizations to introduce new projects to thrive in the industry while surpassing their competitors. Individuals who perform data analysis are called data analysts or scientists. Many other professionals also carry out data analytics in companies as a part of business improvement strategies. Different kinds of data analytics are commonly employed in organizations and they are. 

Data Analytics Process

Data analysis is a process that involves a few steps.

  • The first step is to determine data requirements to group data for future steps. The criterion can be anything as per requirements of the company like demographics, age, gender, or income. The commonly taken data can be numerical or classified by category. 
  • The second step is related to collecting data. You can utilize various sources like online sources, environmental sources, cameras, or computers for the same. 
  • The third step in data analysis is organization of data after collection. The purpose of organizing data is to analyze it to find trends and patterns. Most data analysts use software like spreadsheets that can process statistical data. 
  • The final step is data cleaning before analysis. The organized data is checked and scrubbed to make sure it is free from errors and duplications and that it is complete. This step is usually carried out to identify and rectify errors before it is handed over to a data analyst for data analysis. 

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Types of Data Analytics

As discussed above, data analytics is the involvement of various tools and technologies to help a business improve its performance. There are different kinds of data analytics depending on the purpose of the process and its uses. 

  • Descriptive analytics: The word “descriptive” gives hints about the type of data analytics. It is a form of analytics in which situations that have happened over some time are described. It will help the analysts understand the change in particular departments. For example, an increase in sales can be identified by comparing the results with records. 
  • Diagnostic analytics: Just like medical diagnosis, the analysis that focuses on finding reasons to understand why certain events happened is called diagnostic analysis. Professionals who perform this kind of analytics, consider diverse data inputs and hypothesizing. For example, they try to find out the impact of weather on sales. They also try to get answers to questions like “Did changes in marketing campaigns affect sales?”
  • Predictive analytics: This is a kind of analytics used to predict future outcomes such as ‘Where will the company stand after two years? 
  • Prescriptive analytics: It is a type of analytics that is used to generate a course of action for future progress. It involves making changes to the chosen strategy to improve the performance of the business.

Tools Used in Data Analytics

You need to know the list of commonly used tools in data analytics before reading the IIM SKILLS Data Analytics Course Review. This is suggested for you because it will help you understand the value of the course based on the training given on using the important tools for data analytics.

R programming: R is a programming language and a tool used to perform analytics. It is employed by analysts like you for data modeling and statistics. It will help you to present data in various ways by its manipulation feature. Many individuals consider it a superior tool to SAS as it has advanced characteristics in many aspects such as performance, outcome, and data capacity. It is used to run on different platforms such as Windows, macOS, and UNIX. It has around 12,000 packages and allows users to find their desired packages by category. The best part about R is its facility to provide tools that can install packages as per the requirements of the user. 

Python:  Python is a language used by programmers and data professionals for coding. It is a user-friendly tool; easy to write, maintain, and read. The main reason many individuals choose Python is that it is open-source. Guido van Rossum developed this language in the 1980s to support structured and functional programming methods. Python is similar to many other software like Ruby, JavaScript, and PHP. It is known to have many machine learning libraries like Theano, Keras, Tensorflow, and Scikitlearn. The most favourite feature of Python as per the programmers is its flexibility to get assembled on different platforms such as servers, MongoDB databases, JSON, or SQL. Not only that, it can allow users to use text data as well.

Excel: Almost every employee is aware of Excel. It is because of its popularity, common use, and its usability. You need to know Excel and the statement doesn’t change even if you are a pro using Tableau, R, or Sas. Excel is important to carry out data analytics as per the requirements of the client. Its advanced business analytics option makes it the most appealing software for data analysts. Users prefer Excel to other kinds of tools because of its prebuilt options such as time grouping, DAX measures creation, and automatic relationship detection. 

Tableau: Data visualization is a part of data analytics. If the data analyst is unable to present their findings in an understanding manner, it can take a toll on his job and business profits. This is why most employers suggest their data analysts use Tableau. It promotes the presentation of facts, opinions, and recommendations in an easy way for the audience. Any individual from a non-technical background can see the visual elements presented to them without having to worry about misinterpreting when they are created using Tableau. The creation of pie charts, bar graphs, and other visually appealing structures is possible with the use of Tableau in an organization.

Power BI: This is a kind of scalable and unified platform for enterprise business intelligence and self-service. It allows the users to connect any kind of data for visualization purposes. Power BI promotes end-to-end data protection through which datasets and dashboards are protected. This feature of the tool helps in securing the data if it is shared outside the entity or is in different formats such as PowerPoint, Excel, and PDF. Integration of Microsoft 365, Azure, and Power BI assists in extracting maximum value from data and technology. Users utilize Power BI to tell stories through data visualizations and charts. It is also used to examine “what if ” scenarios within the chosen data. Data analysts can create reports using Power BI that can be used to answer certain questions related to organizations. 

Alteryx: Alteryx is a platform that helps data analysts use data more easily. This tool makes testing, cleansing, accessing, analyzing, outputting, and combining data much easier than Power Query, SQL, Excel, or similar tools. The usage of Alteryx allows teams to develop data processes more efficiently, repeatedly, less risky, and less error-prone manner. The data process can be from a department where the selected data needs consolidation, manipulation, analysis, or testing. Some of the examples across departments include accounting, audit, finance, tax, HR, SalesOps, Marketing, IT, and Procurement/sales chain. 

SQL: The full form of SQL is structured query language. It is a language used for processing and storing information in a database. The chosen database is usually a relational database that is used by data analysts to store data in tabular format with columns and rows to represent relationships between data values and different data attributes. SQL statements are used to update, store, search, retrieve, and remove data from the database. This language is also employed by organizations for the maintenance and optimization of database performance. The main reason for data developers and analysts prefer SQL is its feature to be integrated with other programming languages.

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The Reasons to Implement Data Analytics in an Organization

It is important to know why companies prefer employees to perform data analytics for their growth. Make sure you learn about the benefits of data analytics before you join the relevant courses to make a better career decision. 

Personalized Customer Experience:

Businesses do not collect data from a single source; they access all possible sources to obtain required information including e-commerce, social media, and physical retail. Data analytics assists businesses in gaining insights into customer behavior to offer a better-personalised experience through the creation of comprehensive customer profiles from the collected data. Behavioral analytics models are the commonly created models based on customer data for the optimization of customer experience. 

Informed Decision-making:

Most enterprises use data analytics as a guiding light that can help them make better decisions and reduce the risk of financial losses. This is why predictive analytics is chosen to forecast the future depending on the changes in the operations and portfolio of the business. On the other hand, prescriptive analytics allows enterprise owners to respond to changes in the business. 

For example, a business can experiment with new product offerings and pricing to note their impact on customer choices. Testing the response can help validate the hypotheses generated by such models. The data analysts can compare the sales numbers before and after the changes to identify the success rate and predict the outcomes to assist the decision-makers in improving the business growth strategies. 

Streamlined Operations:

Believe it or not, data analytics are most preferred by organizations because of their ability to improve the efficiency of operations. Collection and analysis of data related to the supply chain can show the data analysts the origination points of bottlenecks and production delays. In simple words, it helps the analyst predict points of concern for the future. For example, if the data professional uses a demand forecast and identifies that a vendor won’t be available for the next period, they can arrange for a replacement or temporarily fill the place. 

Not only that, many businesses have reported facing difficulty in optimizing inventory levels. The usage of data analytics can fix their problem as it can show the optimal supply of products as per the considered factors including holidays, secular trends, and seasonality. 

Risk Mitigation and Handling Setbacks:

Running a business is no easy job. There are a lot of risks involved in managing different departments in a business. Employee theft, customer theft, employee safety, legal liability, and uncollected receivables are some of the business risks. A business owner keen to mitigate risks by taking preventive measures must consider data analytics. Data analytics points at the potential risks allowing the analysts to make appropriate recommendations to the management. 

For example, a propensity model employed by a retail chain can predict events in the future for the determination of stores that have the highest risk of theft. The analyst who is aware of this information can determine the level of security required for the stores. 

That is not all, a business that has experienced losses can use data analytics to prevent financial losses in the future. A business that has overestimated the demand for a specific product can make use of data analytics to set an optimal price for clearance sales to get rid of extra inventory. Another less-discussed benefit of using data analytics is that an analyst can create statistical models that can produce automatic recommendations to resolve existing problems.

Enhanced Security:

It is a fact that almost all the businesses in the market receive data security threats. Organizations can implement data analytics to find out the roots of data breaches in the past by visualizing and processing relevant data. For instance, an IT department can employ data analytics applications to process, parse, and visualize audit logs for the determination of the origins and courses of an attack. The information obtained can be helpful to the IT department in locating and patching vulnerabilities. 

Statistical models are also used by analysts dealing with the relevant elements of an IT department to identify potential attacks and prevent them. The usual attacks are load-based assaults like distribution denial-of-service (DDoS) attacks that exhibit abnormal access behaviour. Organizations that set up these kinds of models and integrate them with alerting and monitoring systems can detect and highlight anomalies to let security professionals take necessary actions immediately.


Directly jumping into reading the IIM SKILLS Data Analytics Course Review is not the ideal way to understand the reputation and quality of services offered by the institute. This is why let us look briefly at IIM SKILLS.

It is an ed-tech company started by Vaibhav Kakkar in the year 2015. The institute’s headquarters are in New Delhi. It has a presence in over 23 cities in the world including Singapore and Dubai. It currently offers courses in marketing, analytics, writing, and finance domains. IIM SKILLS was founded after an educational blog managed by Vaibhav Kakkar hit over 1 million views for its informative content on career guidance. The Content Writing Master Course was the first training program on the digital platform. New courses were introduced after the initial program became a success. 

The mission of the educational entity is to let every learner access high-quality training at an affordable price. It aims to provide training programs to students through its digital presence. It has made a range of self-paced learning courses available for aspiring individuals. The company is always excited to launch upskilling programs as per the market requirements and allow all learners to reach their goals. Most of the courses offered at IIM SKILLS are crash courses that save time for people who cannot attend a full-time program due to their personal and professional commitments. 

It has a good track record of educating students on various concepts and training them on different sets of skills. The mentors at IIM SKILLS have a history of transferring their knowledge to learners for more than a decade. Over 35000 students have been trained by the instructors at IIM SKILLS. The ed-tech company has conducted over 9500 training sessions so far. The courses that were introduced after the content writing master course are the digital marketing master course, technical writing master course, GST practitioner certification course, advanced SEO course, business accounting & taxation course, financial modelling master course, tally master course, certified investment banking course, and data analytics master course. 

Being a student of IIM SKILLS will allow you to enjoy benefits such as certifications, a customer delight approach, virtual interactive classrooms, and lifetime access to study material. These are the main reasons for many famous media channels to feature IIM SKILLS on their news. Entrepreneurs, Financial Express, The Daily Guardian, Business today, Forbes, and The Times of India have shared posts on success stories of IIM SKILLS and about its most fruitful programs. 

IIM SKILLS Data Analytics Course Review

The data analytics course available at IIM SKILLS is named the data analytics master course. Many students who have availed of this 6 months program shared that they gained a range of skills and knowledge related to data analytics from the 160-hour lectures. It is a comprehensive course that includes a range of relevant topics and many important tasks for the learners allowing them to grasp as much information and skill training within a short period. 

The inclusion of practical assignments paves the way for the students to receive feedback from qualified mentors on their performance and improve themselves. As the program is tools-based, it is easier for aspiring data analysts to find a job.  We have discussed a list of tools at the beginning of the article and you will be trained on using all of them. The interest-free EMI option reduces the financial stress of the learner that comes from one-time payment rules. IIM SKILLS includes more than 7 live projects in the course that allow the individuals to get exposed to real-life scenarios in data-related fields. 

Not only that, case studies and assured internships make the course one of the top data analytics courses in India. Separate sessions conducted to prepare students to face interviews and create impressive resumes have proven to help individuals secure a job in reputed companies. Not to forget the shareable master certification that draws career opportunities to flow toward the learners. 

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Conclusion on IIM SKILLS Data Analytics Review

Data Analytics is a method that helps many businesses grow and offer great customer experience. The same reason has created employment opportunities for individuals with knowledge and skills in data analytics. This is why many people are looking for courses that can change their career fate and fulfil their dreams. Most students consider it one of the best training institutes in India. I.e., IIM SKILLS for data analytics program instead of other certification courses. Reading the IIM SKILLS Data Analytics Course Review gives clarity on the chosen career path, which is shared above. 


Q. Is the IIM SKILLS data analytics course tools-based?

Yes. It is. You will acquire the skill to work with a range of essential data analytics tools if you join the course at IIM SKILLS. Python, R, SQL, Alteryx, Tableau, Power BI, Excel, and VBA are the tools covered in the 6-month program. 

Q. Should I have to attend data analytics classes on weekdays if I join IIM SKILLS?

No. All the live classes are conducted on Saturday and Sunday to allow busy learners like you to upskill themselves. 

Q. How many months should I spend to complete the IIM SKILLS’s data analytics master course?

The duration of the course is 6 months. Classes will be arranged on weekends allowing you to focus on grasping concepts on Saturday and Sunday and testing improving your skill set and knowledge on weekdays through practical assignments.