Where is Data Analytics Used? A Complete Guide

It is time to find an address, “Where is Data Analytics Used?” to relieve aspiring data analysts from confusion. Students and professionals who aspire to secure their careers are keen on finding answers to the question. That’s because having a range of streams that use DA will open doors for many opportunities for business analysts and related professionals. In simple words, they no longer have to depend on a single field to earn bread and butter. They can choose any sector that utilizes DA and lead a life without worrying about job security. This article is an answer to the question “Where is Data Analytics Used?”. A glance at data analytics and reliable means to enter the stream is here. Let us begin by grasping its concept and answer your questions.

Data Analytics (DA)

A tool that is used to scan large volumes of data to find patterns and then make decisions is called data analytics. This is carried out with the help of specialized software and systems. Many organizations from different fields use data analytics to find hidden trends and help management in making informed decisions. Researchers and scientists are known to take assistance from data analytics to verify hypotheses, theories, and scientific models. 

DA is the assembling of various analytics such as business intelligence (BI) and reporting and online analytical processing (OLAP). It resembles business analytics in a few aspects. Business analytics is used for business purposes whereas data analytics is employed for a range of purposes. Allowing the management of a company to use data analytics will increase operational efficiency and revenue alongside optimizing marketing campaigns and bolstering customer service efforts. Gaining a competitive edge in the industry by identification and adaptability to changing market trends is possible with data analytics. 

Classification of Data Analytics

It is a vast stream that is further divided into four kinds. The classification of the concept is done as per its nature and purpose.

• Descriptive Data Analysis
• Diagnostic Data Analytic
• Predictive Data Analysis
• Prescriptive Data Analytics

Descriptive Data Analysis: This is the most common method in businesses used for understanding customers and past events. It is a common tool because it is very simple in nature. Large volumes of raw data are given as input to identify patterns to describe the current situation or past events as per the data. You need to choose data for a certain period to obtain the finding from that duration. It can help you figure out the increase in views /sales as per the selected intervals.

Diagnostic Data Analytics: If you want to know why something happened, utilize Diagnostic Data Analytics. Many people directly move to predictive analytics by skipping diagnostic analytics in the data analysis process. This is a crucial step as it will help understand why something happened and take action accordingly because having a set of problems at hand is not enough. The diagnostic analysis will assist the data analysts in figuring out the causes of a failed product or decreased customer satisfaction for an item. If you work in the sales department, ensure to use diagnostic analysis to detect the negative and positive anomalies in the performance of sales. 

Predictive Data Analysis: As the name suggests, it is a method used for predicting future outcomes in the concerned sector. The data given as input must have older data and market trends about the performance of the business. Combining the two will produce outcomes that give the business analyst an idea of how the business will run in the future. For example, this kind of analytics will help the management to predict the success rate of to-be-released videos.

Prescriptive Data Analytics: This is the last type of data analytics that is used for drawing actionable courses from the given data. Businesses utilize prescriptive analysis to improve their performance. This considers the results obtained from predictive analytics and diagnostic analytics and accordingly prescribes the actionable courses. This process is seen as complex by a few. However, it is easy to carry out with sufficient exposure to the analytics types. Businesses that use prescriptive analytics will eventually improve their sales number.

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Application of Data Analytics in Different Sectors

Were you searching for an answer to the question “Where is Data Analytics Used?”  A few sectors which utilize data analytics to the best and improve customer satisfaction levels along with the quality of services. 

• Banking & Securities
• Media & Entertainment
• Pharma & Healthcare
• Education
• Manufacturing
• Insurance
• Transportation
• Government
• Energy & Utilities
• Retail & Wholesale

Banking & Securities:

Many of the parts of banking like retail trade, hedge funds, and big banks employ data technologies to review trade analytics that are used in sentiment measurement, high-frequency trading, predictive analytics, and pre-trade decision-support analytics. Anti-money laundering, risk analysis, KYC, fraud mitigation, and demand enterprise risk management are a few areas that utilize data solutions and data. The involvement of data solutions and data analytics tools helps agencies and banks to keep a check on the changes in the financial market. For instance, stock exchanges use data analytics and data along with network analytics and Natural Language Processors (NLP) to find and regulate active illegal trade practices that take place in stock markets and take disciplinary action against the wrongdoers. 

Media & Entertainment:

People in the current world want to have access to entertainment whenever they want. Also, they have their own content preferences which makes it harder for new companies to survive in the industry. Platforms like Amazon Prime, Netflix, Hotstar, and Instagram are the key players in the present entertainment industry as they provide rich media content with a pinch of personalization. 

If you are wondering Where is Data Analytics Used? Especially In Media & Entertainment, don’t worry. To explain the concept in a better way, let’s look at web scraping. It is a kind of tool used for the collection of data from popular social media channels and for learning about trending tags. The data scraping solutions allow the analyst to gather real-time data to get useful insights like the user’s concern. Companies utilize the collected data for the creation of relatable & interesting content to match the requirements of the target audiences and thereby measure the results and share relevant recommendations to the users. For example, Spotify is known to have used Hadoop’s big data analytics for data collection and analysis from its users and offers personalized recommendations to music lovers. 

Pharma & Healthcare:

Some of the ways implemented in the healthcare and pharma sectors for the improvement of customer satisfaction and medical services are big data and advanced cloud technologies. Remote Patient Monitoring (RPM) and Wearable trackers are examples of improvements in the healthcare industry. This kind of advancement is also helping patients in tracking their treatment plans. 

Both physicians and patients are at benefit as the former group can get insights into a patient’s health to prescribe medications accordingly for the wellbeing of the suffering individuals. To put it short, healthcare professionals can reduce waiting times by improving the care.

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Education:

Believe it or not, the current education industry generates a large amount of data. Many Universities, corporate coaching, courseware, learning methodologies, and schools have implemented advanced solutions and technologies to generate advanced solutions and technologies to generate data that can be used by administrators to chart and graph to derive insights about teaching and learning patterns. Once the patterns are identified, the administrators can improve the gaps. 

The effective use of analytics and data will improve teaching strategies and focus on uninteresting areas of learning to make changes in the courses to grab students’ attention.  The education industry seeks the help of data analytics to enhance learning systems and improve education. Another advancement in the education sector with the use of data analytics is planning school bus routes.

Manufacturing:

Manufacturing industries dealing with different goods and natural resources like oil, metals, gas, agriculture products, and minerals have started generating big volumes of data in the past few years. The generated data is often complex and not so easy to handle. This is why they have become one of the prime candidates for data analytics. 

No wonder adoption of digitalization along with seeking assistance from predictive analytics for transforming industries into data-driven decision makers has become prevalent in the current world. All kinds of precious data including text, geospatial data, IoT data, temporal data, and graphical data is used by companies to analyze and integrate them into datasets to derive useful information.

Insurance:

Most people have the question “Where is Data Analytics Used?”, especially when they have a plan to enter data analytics. Predictive analysis is one of the highly financially invested tools in the insurance sector. Insurance companies make use of the data to increase profitability and sales. A range of sources are considered for data collection. Casualty and property insurance companies use agent interactions, telematics, smart homes, and customer interactions along with a few social media campaigns for the management of their relationships with clients about future customer requirements, underwriting, claims, and many more aspects.  Insurance companies utilize the data insights for the development of new products and thereby achieve improvement in customer services for the generation of higher revenues.

Transportation:

Many concealed opportunities in connection with big data are available in the transportation industry. Governments of different countries make use of large chunks of data for understanding travelers’ requirements, converting cities into smart ones with IoT, controlling traffic, and optimizing route plans along with introducing transport applications and congestion management systems. 

Not just government entities, but even the private sector use big data for improving transportation systems to offer the most-efficient customer experience during corporate meetings, holidays, and other notable stays. Logistics companies have also entered the race and they are keen on using data analytics in fasting operations, revenue management, and trying to gain a competitive edge in the industry. In simple words, massive changes have come and will continue to enhance the transportation industry. 

Government:

Many government institutions and government bodies benefit from analytics in various ways. Government is on a mission to utilize big data to improve customers’ satisfaction levels and services in almost all public services sectors like health-related research, financial market analysis, environmental protection, energy exploration, and fraud detection. An example is the use of analytics in the drug and food administration department for the detection and identification of patterns in the rise of food-related illnesses and diseases. 

Energy & Utilities:

Advanced technologies and big data have extremely been helpful for the companies that are present in the energy & utility sector. Data analytics has proven its significance in improving decision-making insights and management advances. Some of the examples proving the same are

• The use of analytics has become rampant in companies that are focused on determining energy saving and energy consumption. Application of data analytics for the same promotes management of power outages and identification of peak times for skillfully drafting energy pricing. 
• Many firms from the Oil & gas industry have started using data solutions for driving refinery, real-time adjustments, and distribution processes to market demands. 
• Several energy organizations are employing data for smart grid regulations and management. Increasing the efficiency of renewable energy sources like solar and wind power is done by the optimization of weather predictions along with the integration of advanced tools and technologies like machine learning algorithms. 

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Retail & Wholesale:

The retail and wholesale companies largely depend on greater customer satisfaction and margins. There is a lot of competition in the market and retailers have started employing DA to handle big data for accurately anticipating customer needs and then offer things that can help them. Retailers consider DA in staying in the market by dealing with fierce market competition. They use data analytics solutions to collect detailed insights to satisfy their customers and make them revisit their stores. Let us look at aspects where retailers use it.

• Personalization of customers’ experience and enhancement of marketing
• Optimization of logistics and supply chain management
• Management of prices for the maximization of sales
• Best use of retail data analytics

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Data Analytics Courses for Beginners

We have seen the answer to “Where is Data Analytics Used?” and learned the basics of data analytics. Now, get yourself ready to know the details of two education providers that offer data analytics programs for freshers.

Dataquest:

Dataquest is a well-known organization that is determined to help learners upskill themselves in the most efficient way. It offers courses on many topics, Python, R, Power BI, SQL, Excel, Tableau, and many more. Exercises are specially designed to assist the students in understanding where they stand and what they must do to get better. If you want to become a data scientist, data analyst, data engineer, or business analyst, visit the Dataquest website.  

“Data Analyst in R” is one of the best courses. You will acquire and develop R skills to become one of the critical resources for your company. This program will help you explore & extract data using R. It will also give you the required knowledge to create data visualization. The presence of world-class pedagogies will allow you to draw meaningful insights from data. 

Course Curriculum

• Basics of R
• Data Visualization using R
• Data Cleaning using R
• Use of SQL to Work with Data Sources
• Web Scraping & APIs in R
• Statistics and Probability
• Machine Learning and Predictive Modeling in R
• Shiny Applications in R

Course Highlights

• Project Portfolios
• Certification
• Exercises

Course Details

Fees: Free

Duration: 4 months

Contact Details

Visit the Dataquest website and use the query submission option to clear your queries. 

IIM SKILLS: If you are determined to improve your career, then select IIM SKILLS as your training institute. This ed-tech company is not just known for data analytics courses but also a range of other programs such as “Technical Writing Master Course, Digital Marketing Master Course, Certified Investment Banking Course, and CAT coaching”. 

Many passionate learners choose IIM SKILLS because of the offered job assistance and high-quality training. Almost all training programs at IIM SKILLS have an internship attached to them. The internship opportunity is to allow learners to practice theory in the real world.  The courses are led by instructors who are highly experienced and qualified in the industry. They make sure to clear the queries of all the students letting them feel valued and heard. 

Course Curriculum

• Use of Advance Exce
• Use of VBA
• Use of SQL
• Use of Power BI
• Use of Python
• Use of Tableau
• Use of R in
• Use of Alteryx

• Access to Premium Tools
• Master Certification
• Access to LMS
• 24×7 Support
• Practical Learning
• Case Studies
• Live Projects
• Internship

Fees: ₹ 49,900 + Taxes

Duration: 6 months including 2 months non paid internship

• Financial Modeling Course
• Digital Marketing Course
• SEO Course
• Technical Writing Course
• GST Course
• Content Writing Course
• Business Accounting And Taxation Course
• CAT Coaching
• Investment Banking Course

Contact Details

Phone: _91 9580 740 740

Email: [email protected]

Conclusion

Data analytics has many applications in several streams. The reason for using an online search engine to find the application of data analytics in different realms is the scope for job security. Recession can hit any time and it is the responsibility of the individuals to be prepared to face it. If there is a lay-off period going on in one industry the employee must search for opportunities in sectors that have openings to render their services. 

• Banking & Securities
• Media & Entertainment
• Pharma & Healthcare
• Education
• Manufacturing
• Insurance
• Transportation
• Government
• Energy & Utilities
• Retail & Wholesale

FAQs

Q. Where is Data Analytics Used?

Many industries benefit from the use of data analytics. Some of the sectors are actively using and will continue utilizing the data analytics tools are.

• Banking & Securities
• Media & Entertainment
• Pharma & Healthcare
• Education
• Manufacturing
• Insurance
• Transportation
• Government
• Energy & Utilities
• Retail & Wholesale

Q. Is it a good choice to choose IIM SKILLS’s Data Analytics Master Course?

Yes. IIM SKILLS is an institute that is known to provide high-quality education with the help of top-notch faculty. Data Analytics Master Course is a 6-month course that has a valuable add-on: job assistance. If you are a busy professional or a student, you can avail of this course to save time and effectively learn the concepts in Data Analytics. The Non-paid internship will expose you to some of the real-time cases in the industry and make you familiar with the practical application of the subject.

Q. Who can apply for a Data Analytics program?

Anyone can learn the technicalities of data analytics. Many colleges and relevant educational entities have come to the rescue of the individual who is passionate to acquire knowledge and skills related to data analytics. There are undergraduate programs, postgraduate programs, and crash data analytics courses. All you have to do is pick the right institute and fulfill your dreams.