Top Data Analytics Courses By NIIT With Practical Training

Name: Data Analytics Master Course
Brand: IIM SKILLS
SKU: DAMC-07/23
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August 7, 2023 Arka Roy Chowdhury Courses, Data Analytics

This article intends to make you aware of the numerous data analytics courses by NIIT. This we will discuss later. First let us know what data analytics stands for, its uses, why it is essential, and, why companies hire data analysts.

What Do You Mean by Data Analytics?

Data analytics is the process of assessing raw data from multiple data sources to derive insightful conclusions

Defining Data Analytics

Extrication of the maximum value from the volume, veracity, and velocity of data produced nowadays is crucial. Today more than ever, analytics are important. The practice of using varied data sets to uncover important insights in the sort of trends, patterns, and relations is known as data analytics. Both qualitative and quantitative techniques must be applied. You can acquire, clean, store, analyze, and report data on any scale using analytics software.

It is a field that entails evaluating data sets to acquire information that might be used to address issues in various industries. To provide accurate data analysis, it makes use of several academic fields, including mathematics, computer programming, and statistics. Data analytics may be used to explain, forecast, or improve a company’s performance. They accomplish this by explaining, forecasting, and resolving current and future problems utilizing advanced data management techniques like data transformation, data mining, data modeling, etc. These objectives set data analysis apart from related fields like business analytics and data science. Only businesses employ business analytics, a type of data analytics. Through in-depth understanding and strategic oversight, data analytics and data science help solve challenges.

Top Uses of Data Analytics

Transportation

By enhancing systems and systems for transportation intelligence, one can employ data analytics to reduce traffic congestion and enhance travel. It performs by gathering massive amounts of data to create other routes to mitigate traffic jams. As a result, fewer accidents on the roads would result from fewer traffic jams. To enhance their package, travel agencies can also learn about customers’ preferences from social media as well as other sources. Customers’ travel experiences would be enhanced, as would the customer base of companies. For instance, during the 2012 London Olympics, data analytics were utilized to address the 18 million people’s transportation issues.

Education

Data analytics can be used by policymakers to enhance management decisions and learning curricula. Both administrative management and learning experiences would be enhanced by these applications. They can gather preference data from every student to design a curriculum, which will enhance the syllabus. This would improve the system by allowing students to study the same content in several ways. Additionally, quality data collected from students can aid in making more informed decisions on how to allocate resources and sustainable management. For instance, data analytics might inform administrators of which facilities students use the least or which subjects they are not interested in.

Internet Web Search Results

Analytics are used by search engines like Google, Bing, and Amazon e-commerce search to organize data and deliver the most relevant search results. This means that the majority of search engine operations utilize data analytics. Data analytics takes enormous amounts of data given by various pages and organizes it into keyword-based groupings when storing online data. Analytics also aids in ranking websites based on relevance within each group. In giving search results, every word the user types in acts as a keyword. Once more, data analytics is utilized to search a certain collection of web pages and present the one that most closely fits the term intent.

Digital Advertising and Marketing

To know their audience and achieve high conversion rates, marketers use data analytics. In these two sub-users, each involves a variety of data analytics-based activities. Digital advertisement specialists employ analytics to determine the intended audience’s age, dislikes, race, likes, gender, and other characteristics too better understand them. Additionally, they divide their audience using this technology by their preferences and behaviors. Experts also use data analytics to uncover trends and create pertinent content for long-term interaction to achieve high conversion rates. They do this by analyzing analytics trends to assess purchasing habits and frequency.

Delivery and Logistics

In the logistics sector, data analytics are utilized for efficient workflow and improved delivery procedures. As a result, the industry has performed better, which has led to a larger base of customers. By allowing real-time sharing of data of the organization’s insights across partners, it boosts productivity. These findings show changes in customer demand as well as the productivity of employees. Logistics organizations employ data analytics for route optimization to enhance the delivery procedure. This makes it easy for companies to choose the optimal routes and times utilizing individual timetables, Global Positioning System (GPS) data, road maintenance data, and weather data.

Security

To discover potential instances of crimes or security breaches, security personnel use data analytics, particularly predictive analytics. They may also look into recent or continuing attacks. With analytics, it’s feasible to examine other potential security flaws, the behaviour of end users or compromised devices, and how IT systems were compromised during an attack. To keep an eye on neighbourhoods with high crime rates, several cities use data analytics. They keep an eye on crime patterns and forecast the likelihood of new crimes from them. Without endangering the lives of police personnel, this aids in maintaining a safe city.

Fraud Detection

Data analytics is used by various companies across numerous industries to identify fraudulent activity. Finance, pharmaceutical, tax, banking, and retail are a few of these sectors. Predictive analysis is used to evaluate the reliability of individual taxpayer tax returns to spot tax fraud. This kind of analytics is used by the Internal Revenue Service (IRS) to forecast upcoming fraud. Additionally, it is utilized to detect bank fraud through communication analysis. Data analytics is a technique that banks employ to stay in touch with their customers. They can use data analysis algorithms to spot fraudulent activities based on data records of earlier communications with a specific customer.

Enhance Decision-making

Data analytics can be used by companies to avert financial losses. If an adjustment is made, predictive analysis can forecast future customer behaviour, and prescriptive analysis can advise how to react to these modifications to maximize profit. Let’s imagine, for example, that a company wants to raise the prices of its products. To establish if this adjustment might have an impact on customer demand, they can create a model. Testing can verify the model’s conclusions. This would stop poor financial decisions.

Enhanced Business Performance

Data regarding the supply chain can be collected and evaluated to identify manufacturing bottlenecks, delays, and potential future issues. Data analytics may assist in determining the best supply for all of an enterprise’s products when it comes to inventory levels. This makes it simple for businesses to recognize problems and find speedy solutions.

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Why Data Analytics is Important

Minimize the Operating Cost

Even though hiring a data analyst may be costly, the benefits outweigh the cost over time. With the help of effective data analysis, you can carry out additional tasks that could end up saving you a ton of money, guaranteeing data security, and reducing financial risk. Data analytics is also used by organizations to identify the function that consume more financial resources than they should and others that demand greater funding. As a result, technology eventually takes the role of manual tasks in production and operations, which helps to reduce costs.

Forecast Upcoming Trends

With the use of data analytics, companies may forecast upcoming trends and transformations. Companies can create services and products that are future-oriented utilizing predictive analysis tools, helping them to dominate their market. These companies can produce demand for these offerings and increase their market share by using effective marketing. To maintain an edge over rivals and make more profit, they can even secure patents for cutting-edge inventions.

Tracking Product Performance

Analytics of data is used to monitor customer behaviour toward services, products, or both. It can help you figure out why sales are down, what people purchase and why they purchase it, how much they paying for it, how to sell more products effectively, and many other things. Researching customer behaviour aids organizations in making financial decisions, such as adjusting product prices or identifying a niche that they can target.

Solidify Security

Data analytics is used by businesses to review previous security breaches and identify the vulnerabilities that caused them. IT professionals can analyze, interpret, and visualize audit logs with the aid of analytics tools to pinpoint the source and roadmap of security breaches. Using analytical models that recognize anomalous or abnormal behavioral patterns, can also avert future attacks. To detect attempted breaches and warn security experts, these models can be set up with tracking and alerting systems.

Handle Risks

Risks in business can include employee or customer theft, legal liability, havinMakes Improved Business Decisions an excessive amount of inventory of goods, and more. Data analytics aid in risk management and prevention for businesses. A retail chain, for instance, may use a propensity model to identify which outlets are most likely to experience theft. This would aid in determining whether to relocate the store or enhance security.

10 Reasons Why Data Analyst Jobs are Most Wanted?

Makes Improved Business Decisions

Such a person acquires and analyses data sets to conclude. They can accurately assess the business’s current state based on the findings. If a company’s status is not favourable, they might decide how to make it better.

Can Forecast Future Trends

These individuals acquire the data and analyze it to look for patterns to determine trends. They can forecast likely upcoming trends based on previous trends and statistical analysis.

Helps in Strategizing

Predictive analysis can be used by data analysts to create strategies. These plans are created with an eye on future market trends.

Makes Procedures More Effective

The amount of data that can be analyzed by data analysts is enormous. Through the analysis of the data, many insights can be gained, accelerating the efficiency of the procedure. Saving time as a result.

Keeps an Eye on Behavioural Changes Among Customers

Data analysts can evaluate customer behavior toward services or products and how it has changed over time. Companies may now adjust to trends more quickly and easily thanks to this.

Helps to Expand the Customer Base

As soon as an organization starts monitoring customers’ behavior, it can change products to suit the demands of customers. This draws customers who will stick with the brand over time.

Helps Companies to Avert Losses

Companies utilizing this technique have an advantage since the predictive analysis can forecast future results. They can stay away from funding projects and methods that the analysis indicates are not likely to be successful.

Can Work for Any Industry

Data analysis is used in practically every domain of any industry. Jobs for data analysts are in high demand because data is one of the most precious assets at the moment.

Data Analyst Jobs Pay Well

During the early stages of their careers, data analysts might earn up to Rs. 11.1 lakhs on average per year. In India, an analyst receives a yearly salary of Rs. 4.3 lakh. Data analyst roles are in high demand because of the attractive salary range.

Have a Lucrative Career

Data analysis is important because so many organizations are now running based on data. This is the reason why there will always be a need for data analysts.

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Now We Will Discuss the Two Best Data Analytics Programs Offered by NIIT

Course Name – Advanced Professional Data Analytics Courses by NIIT

This comprehensive Data Analytics Course by NIIT has been designed after taking into account the requirements to perform essential duties and tasks like data mining, and data extraction, to pull out workable insights for companies. With the help of the two-level advanced Data Analytics Courses by NIIT, you will not only become a data analytics expert but also get ready for data analyst jobs. As the course completes, you will earn a certification for StackRoute. Moreover, you will also equip yourselves with behavioural and engineering skills. That you will do this with the help of a capstone assignment using practical projects.

Skills You Will Learn in the Advanced Data Analytics Courses by NIIT Are as Follows:

RDBMS, Data Visualization, Data Analysis, Python, SQL, and, Tableau

Features of the Advanced Data Analytics Courses by NIIT Are as Follows:

Explore several job opportunities
Get prepared for entry-level job posts and roles like Data Analyst
Self-learning
Inter-personal Skills
Efficient interactions with Clients
Listening Skills
Presenting Skills
Working as a team
Isolated work environment
Isolated work practice
Corporate work ethics and culture

Primary Technological Skills Needed for the Thorough Data Analytics Courses by NIIT Are as Follows:

Data Visualization & Analysis through Microsoft Excel
Analytics through SQL
Data Visualization and Statistics through Python
Exploratory Data Analysis through Tableau
Programming through Python

The syllabus of the Comprehensive Data Analytics Courses by NIIT is as Follows:

Level 1

Course 1 – Data Analytics through Microsoft Excel

Carry out fundamental Data Analysis through Microsoft Excel
Calculate Central Tendencies through Statistical Procedures
Data Visualization through Microsoft Excel
Calculate the correlation and spread of Data

Course 2 – Analytics Through SQL

Building Inhabit data & Database Objects
Query data through SQL
Recover data from numerous Tables

Course 3 – Introducing Programming Through Python

Dealing with the Python explainer
Decision-making with provisional statements
List operations and Interactive statements
Coiling over data organizations
Writing sectional programs within Python

Course 4 – Using Python for Data Science

Creating & controlling arrays through NumPy
Creating & controlling Data Frames and Series
Controlling Data Frames
Advanced Data Frame Handling operations

Part 2

Course 5 – Data Visualization and Statistics Through Python

Descriptive analysis through Python
Forecasting through Probability
Distribution & Sampling processes
Distinct Probability Circulation
Constant probability Circulation
Hypothesis Examining through Z Test
Hypothesis Examining through T-Test

Course 6 – Exploratory Data Analysis (EDA)

Customer Churn Assessment for Banks Using EDA
EDA to reduce IBM employee churn
EDA first case study

Course 7 – EDA First Case Study

Understanding the application of Tableau
Creating Visualizations through Tableau
Knowing Time Series Data
Visualization Dimension and connectional Data
Visualize Data Circulation and Build Dashboards

Course 8 – EDA Through Tableau – Second Part

Designing Advanced Dashboard
EDA with the help of Visualization

Level 2

Part 1

Course 10 – Assignment

Carryout EDA
Visualizing & presenting insights

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Now Let Us Move to the Next Advanced Data Analytics Courses by NIIT

Course Name – Data Analysis and Visualization through Power BI and Microsoft Excel

This advanced Data Analytics Course by NIIT has been designed keeping in mind the various uses of MS Excel to analyze data and visualize the same with the help of advanced MS Excel functions and operations. Besides that, you will also learn how to manage data through Power with the advancement of intricate data visualization in MS Power BI. You will also learn how to create and present dashboards in MS Power BI.

Highlights of the Advanced Data Analytics Courses by NIIT Are as Follows

The duration of the advanced Data Analytics Courses by NIIT is 38 Hours
Forms of the advanced training for Data Analytics Courses by NIIT are classroom plus online and classroom plus mobile application-based training
Experienced faculty from the industry
Faculty guides through the mobile app
First-hand use of tools
Learn assessing data and visualize data through Advanced MS Excel
Learn to create & present dashboards in MS Power BI
Extensive study hours, including 36 hours of online mentored practicing sessions for enhanced learning and improved memory in addition to 38 hours of classroom instruction, including the classroom evaluation
Hybrid learning with weekly practicing quizzes on mobile devices, guided practice, and classroom sessions

The Learning Goals of the Comprehensive Data Analytics Courses by NIIT Are as Follows:

Studying the application of MS excel in Data Visualization and Analysis
Using pre-added MS Excel functions and user-defined formulae to or for data analysis
Employing MS Excel Data Analysis tool sets for the application of data analysis
Creation and customization of charts within MS Excel for the use of data visualization
Data Visualization within Power BI
Comprehending the user interface of Power BI and Power BI Variations for example Power BI Web and Desktop
Utilizing Data from MS Excel within power BI for the use of visualization
Dashboarding or reporting through Power BI
Presenting Power BI Dashboards
Data connections and queries in Power BI
Data Conversions in MS Power BI

Modules of the Flexible Data Analytics Courses by NIIT Are as Follows:

Performing Data Analysis within MS Excel
Visualization through Power BI

Eligibility of the Rigorous Data Analytics Courses by NIIT is as Follows:

Possess a working understanding of Microsoft Excel and the Windows platform
Must have studied statistics or mathematics or had any of the two subjects in Class 12

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Frequently Asked Questions

Q1. What is the salary of a data analyst on average per annum?

In India, a data analyst with one to four years of experience can expect to make a gross salary of Rs. 396,128, while a mid-career data analyst with five to nine years of experience can expect to make up to Rs. 603,120. And if you are an experienced senior data analyst who has worked in the field for 10 to 19 years, you can expect to get an average annual salary of Rs. 900,000. However, the salary mostly is based on the company you are working in and where it is based.

Q2. What is the role of a data analyst?

Their usual functions include the following

Using specialized tools to extricate the data required
Replying to queries about data and monitoring them
Assessing data to recognize trends
Establishing systems and methods to make the process of handling data more effective

Q3. What makes the two data analytics programs offered by NIIT special?

The first data analytics program that has been mentioned is a part-time course that has been specially designed for those working employees who do not have time on their hands. The second is a full-time course for everyone.

Conclusion

Being a premier institute, NIIT offers one of the most tempting data analytics courses. You can go through them and decide which program is best for you to pursue. Both programs are exceptional on their own.

Author: Arka Roy Chowdhury

Arka Roy Chowdhury has done his post-graduate diploma course from Asian College of Journalism. Previously, he has worked at a few publications. Currently, he is an intern at IIM skills. Arka is an avid reader of sports and entertainment news.