IIM SKILLS vs. SRM University Data Analytics Course Review

by | Nov 2, 2024 | Courses, Data Analytics, Institute Review

Are you aspiring to a career in data analytics? Read the article below- IIM SKILLS vs. SRM University Data Analytics Course to know in detail about your desired career option in the technical industry. You will get a detailed understanding of the course in Data Analytics, syllabus, eligibility for enrolment, job profiles, and introduction to two reputed educational institutions.

IIM SKILLS vs. SRM University Data Analytics Course

Data analytics is a series of mechanisms to handle data sets with the aid of various software or specialized systems to derive conclusions from them. Data analytics is now one of the most important aspects of commercial industries. Based on scientific data and research, data analytics enables firms to make better-educated business decisions.

Data analytics can help a firm enhance its operational efficiency and customer service, obtain a competitive advantage, and generate revenue tools. Data Analytics tools process and generate results from historical or real-time data.

Two data analytics approaches are exploratory data analysis (EDA) and confirmatory data analysis (CDA). EDA seeks patterns and relationships in data, whereas CDA investigates the veracity of hypotheses about data collection.

Data analysis can be classified as quantitative data analysis, qualitative data analysis, data mining, predictive analytics, and machine learning.

After completing a data analytics degree, candidates can apply for professions such as data engineer, data scientist, data architect, database administrator, and data analyst, with beginning salaries of Rs 4-5 per lakh annum or more.

The Advantages of Enrolling in A Data Analytics Course 

Data has the potential to provide significant value to enterprises, but the analytics component is required to unlock that power. As the importance of data analytics in the business world grows, so does the need for organizations to understand how to use it.

Simplifying Operations 

Data analytics can assist organizations in improving operational efficiency. Data collection and analysis of the supply chain might show manufacturing delays or bottlenecks and help identify potential future problems. If a demand forecast suggests that a specific vendor will be unable to handle the volume needed for the Christmas season, a company may supplement or replace this source to avoid production delays. Furthermore, many businesses, particularly those in the retail industry, struggle to optimize inventory levels. Data analytics can help determine the optimal supply for all of an enterprise’s services based on factors such as seasonality, vacations, and secular tendencies.  

Better Decision-making Based on Information

Companies work curiously for better reasoning based on information and these are dependent on accurate forecasts.  Data is a combined decision of artificial intelligence, machines, and mining study. Predictive analytics can forecast what reaction happens to changes in the business and recommend how the organization should respond to dynamic changes. Furthermore, organizations can utilize data analytics tools to measure the success of changes and visualize the results, It allows in crucial decision-making and implementing the possible changes across the organization.

Satisfy the Customer Experience

Customer satisfaction is part of the business. Businesses can forecast their marketing pattern after data collection through a variety of digital methods. It includes physical retail, e-commerce, and social networking. By using data analytics to construct entire customer profiles from this information, businesses may get insights into consumer behavior and provide a more personalized experience. Consider a retail clothes store that has a physical locatDesign well as an online presence. The corporation might analyze its sales data with data from its social media pages, and then create targeted social media campaigns to increase e-commerce purchases for product categories in which customers are already interested. Organizations can improve the customer experience even further by running behavioral analytics models on customer data.  

 Stronger and Effective Marketing

What distinguishes firms is the distinct method they take to market their products. Companies can use data analytics to ascertain customers need. Data allows organizations to do in-depth research in market trends for targeted marketing. 

Reduce Risk and Deal With Setbacks

There are risks everywhere in business. Among them are customer or employee theft, uncollected receivables, worker safety, and legal liability. Data analytics can assist a company in evaluating risks and taking preventative steps. A retail chain, for example, may use a propensity model, which is a statistical tool for forecasting future behaviors or occurrences, to determine which stores are most prone to theft. The firm may then use this information to assess the level of protection required at the stores, as well as if it should divest from any locations.  

Increase Security

Data security concerns affect all businesses. The IT department, for example, can use data analytics programs to parse, process, and visualize audit logs to determine the path and origins of an incident.  Furthermore, IT departments can use statistical models to prevent future attacks. Attacks usually involve anomalous access behavior, particularly in load-based attacks such as a distributed denial-of-service (DDoS) attack. Organizations can set these models to run indefinitely, with monitoring and notification systems built on top to detect and report anomalies so that security professionals can respond quickly.

Qualifications for Data Analytics

Qualifications are an important component of laying a firm basis for any career. The more qualified a candidate is, the more likely they are to be employed by top organizations and receive a competitive salary. To become a Data Analyst, candidates can pursue undergraduate or postgraduate degrees in fields such as Economics, Statistics, Data Science, and Computer Science.

However, students from any educational background can enroll themselves in data analytics diploma or certification courses. A Bachelor’s degree with at least 50% marks in aggregate or equivalent, preferably in Science or Computer Science, is required for admission to any Data Analytics course.

Data Analytics Skill Set Requirements

A good data analytics practitioner must have strong analytical and numerical skills. Aside from that, a complete understanding of computer software(s) such as Querying Language (SQL, Hive, Pig), programming Language ( Matlab, Python, etc.), Statistical Language (R, SAS, SPSS), and Excel is required. Data analytics experts must also have strong interpretive approaches and problem-solving abilities to explain the data analysis reasoning, process and its results.

Job Description and Profiles for Data Analyst

A Data Analyst is a professional who gathers and analyzes data across the organization to make educated judgments or to assist other team members and leadership in making sound decisions. Responsibilities include:

  • Data analysts are responsible for interpreting data and analyzing outcomes using statistical techniques.
  • Creating and putting into action data analysis, data collection systems, and other initiatives to improve statistical efficiency and quality.
  • Obtaining information from primary or secondary sources and keeping databases

Category or Specific Industry in Data Analytics Jobs-

Analysts can obtain jobs in a variety of fields, including:

  • Medical and health care
  • Market research
  • Business
  • Market reasoning
  • Operations research

Responsibilities

  • Create records management policies and procedures
  • Discover areas for process improvement and automation
  • Development and oversight of automated data processes
  • Locate, evaluate, and apply external data validation and cleansing services and technologies
  • Create and monitor key performance indicators
  • Create and support reporting procedures
  • Inspect and audit data quality
  • Communicate with internal and external clients to completely comprehend data content
  • Using suitable tools and procedures, collect, comprehend, and document precise business requirements.
  • Survey design and execution, as well as survey data analysis
  • Manipulate, analyze, and comprehend complex data sets related to the employer’s company use of business analytics reporting technologies to generate reports for internal and external
  • Design data dashboards, graphs, and visualizations
  • Mine and analyze massive datasets, derive valid inferences, and successfully communicate them to management using a reporting tool.

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IIM SKILLS vs. SRM University Data Analytics Course 

IIM SKILLS – details

IIM SKILLS is a well-known and one of the highest result-oriented online educational platforms. It offers 6 monthly data analytics course in online study mode under the supervision of well-qualified teachers (working or retired industry experts) with lifetime study access to study content.

Other Professional Courses from IIM SKILLS

Modules

Excel in detail: Basics and Advanced

  •  Introduction to Excel setup, Setting up, and Conditional Formatting
  •  Data Sorting, Understand, and Validation
  •  Understalinesg Name Ranges
  •  Chart layout
  •  Creating and personalizing advanced charts – thermometer charts, waterfall charts, population pyramids
  • Data analysis with pivot tables – usage of row and column shelves, values, and filters
  •  Differences between data layering and cross-tabulation, summary reports, benefits and drawbacks
  •  Change the aggregation kinds and summarization.
  •  Making groups and bins in pivot data
  •  Calculated field concepts, applications, and restrictions
  •  Changing report layouts – outline, condensed, and tabular forms
  •  Creating summary reports 

The Operating Pattern and Components of a Visual Basic Application

  • Visual Basic Application Components and Workflow
  •  What is Logic in VBA?
  •  Exposure to Macro Recordings, IDE
  • Fundamental of VBA Language Elements
  •  Phrases and syntax, Programming assertions, Variables and Data types
  •  Working with Range Objects
  •  Programming & Control Structures, 
  • The looping process, Structures, 
  • Spreadsheet & The workbook Functions, Automatic Procedures, and Event
  •  Key Components and Memory Arrangement and Management in VBA
  • Communicating with Your Users- Basic Dialog Boxes and User Forms
  •  Using User Controls and extensions
  •  Accessing Macros via the User Interface
  •  Using VBA, retrieve information from an Access database in Excel.

SQL

  • SQL – A Quick Introduction
  •  Installation of MS SQL Server 
  •  Introduction to Server Management (SQL)
  •  Comprehend basic database concepts
  •  Getting knowledge of Insertion, Updation, and deleted statements
  •  Introduction of statement option– Subsetting, Sorting, Removing Duplicates, grouping and aggregations, etc
  •  SQL Functions (Number, Text, Date, etc)
  •  SQL Keywords Introduction
  •  SQL Operators – Relational
  •  Basics comprehension of SSIS
  •  Through learning of Packages
  •  Parameters and Visualisation
  •  SSRS Visualisation 

Power BI

  • Power BI Introduction and Power BI Installation
  • When working on a project, introduce several options in the Power BI Desktop Task pipeline.
  • Connect to and retrieve data from many sources (CSV, Excel, and so on).
  • Data cleansing with Power Query
  • Text, Date, and Numeric Power Query Functions
  • Conditional Columns in Power Query
  • Query Editor can be used to clean and manipulate data.
  • Define the granularity of your data.
  • Data Combination – Merging and Appending
  • Fill Down, Grouping, Transpose, Unpivot, Data Types, Replace Errors and Values in Power BI
  • DAX Calculated Tables, Columns, and Measures Overview
  • DAX Time Intelligence
  • DAX functions that are frequently used in real-time (Calendar functions, Filter functions, Information functions, Text functions, Logical functions, Math functions, Parent and child functions, and so on).
  • Power BI Reports Evolution
  • Working with a Variety of Visuals/Charts
  • Formatting Options in Reports
  • Filter visualizations with a slicer.
  • Working with Filters 
  • Download and use Custom Visuals from the Gallery.
  • Include an R or Python visualization.
  • Work with key performance indicators

Python

    • Statistics Basics
    •  Central tendencies measurements
    •  Variance measures
    •  Frequency measurements
    • Matrices Operations
    •  Calculus Fundamentals
    •  Integration and Derivatives
    •  Maxima and minima
    •  The area behind the curvature
    •  Optimization theory
    •  Python pre-installed Text, numeric, date, and utility functions
    •  Lambda functions are user-defined functions.
    •  The concept of applying functions
  •  Python Objects

NumPy (Numerical Python) Processing

  • NumPy functions and methods overview
  •  NumPy data structures
  •  Array creation and initialization
  •  Arrays reading from files.
  •  Functions for special initialization
  •  Indexing and slicing
  •  Array reshaping
  •  NumPy Mathematics

Data operations in Pandas (Series and Data structures)

  • What is Pandas, and what are its purposes and methods?
  •  Data Structures in Pandas (Series and Data Frames)
  •  Designing Data Structures

Tableau Product, Measurement, and Dimensions

  • Architecture by Tableau
  • Connecting to Data and an Overview of Data Source Concepts
  • Understanding the Dimensions and Measures of the Tableau Workspace
  • Default Data Types and Properties
  • Shelves and Signs Tour Card with Show Me
  • Save and distribute your work overview
  • Describe the scope and direction.
  • Running / Cumulative calculations, % of Total
  • LOD (Level of Detail) Expressions: An Overview
  • Table calculation user applications
  • Date Parts and Aggregations
  • Tabular and cross-tab charts
  • Subtotals and totals
  • Stacked Bars and Bar Charts
  • Forecasting, Scatter Plots, Edit Axis, Reference Lines, Filters, Context Filter
  • Individual axes, blended axes, dual axes, and combination charts are all available.
  • Working with aggregate data as opposed to disaggregate data

R for Data Science is introduced, and data can be exported in a variety of formats.

  • Introduction R Package Concept – Useful Packages (Base and Other Packages)
  •  Data Types and Structures (Vectors, Matrices, Factors, Data Frames, and Lists)
  •  R Built-in Features
  •  Text, number, date, and utility
  •  R Functions Defined by the User
  •  Aggregation/Summarization
  •  Data Import from Various Sources
  •  Data Exporting to Various Formats
  •  Viewing Data (Viewing Partial and Complete Data)
  •  Date Values – Variable & Value Labels
  • Adding New Variables (Calculations and Binning)
  •  Creating a dummy variable Using transforms
  •  Handling duplicates and missing items
  •  Filtering and Sorting
  •  Submenu (Rows/Columns)
  •  Appending (adding a row or column)
  •  Merging/Joining (Left, Right, Inner, Full, Outside)
  •  Type conversions of data
  •  Formatting and renaming

The Data Analysis course at IIM Skills establishes abilities with the help of a detailed curriculum in its students to build industry-relevant professionals which allows them to find lucrative job opportunities in the market.

Course Fee:  INR 49900 (inclusive Taxes)

Placement: 100% Job & Interview Support.

Study material access: Lifetime access to study materials (all live and recorded Sessions)

Tools Access:  Lifetime access to all the tools

Faculty support: Faculty support in doubt clearing and other guidance

Refund policy: Money back guarantee if not satisfied with teaching pattern.

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SRM University Chennai

SRM Institute of Science and Technology is one of the top-rated universities in India, with over 52,000 full-time students and more than 3200 staff across all campuses. The University positions itself as a leading academic institution with global influence and is committed to being a leading player in the academic world through excellence in teaching and research while valuing academic freedom and adhering to the highest academic integrity standards.

SRM offers data analytics course in the certification category. 

Curriculum

  • Introduction to Big Data
  • Data Analysis using R
  • Machine Learning
  • Python for Data Science
  • Hadoop and Map Reduce

Program Name – Big Data Analytics

Course Duration: 6 Months

Fee:  1,00,000/-

Apart from certification, SRM offers a BCA in data science. It is a three-year undergraduate degree in data science, machine learning, and artificial intelligence. The program gives students a solid foundation in computer science, statistics, and mathematics while also teaching them how to use these principles to address real-world problems using data-driven techniques. Graduates of the program can go on to study data science, machine learning, artificial intelligence, or other related subjects, or they can work in industries such as finance, healthcare, marketing, and technology. Other job options include research and development, project management, and teaching.

Eligibility

  • A pass in 10 + 2 (Higher Secondary) with one of the core topics being Mathematics/Business Mathematics/Statistics/Allied Mathematics.

(OR)

  • A diploma in engineering (10+3 / 10+2+2 Pattern) from a government/competent authority recognized. (Aggregate Minimum of 50%) MCA and MSc ADS degrees.

Annual Fees: 95,000/-

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Conclusion of This Read- IIM SKILLS vs. SRM University Data Analytics Course

Analytics specialists in the field require knowledge of much more than just how to deal with data and solve problems.  Communication abilities are essential for any career because analytics experts play key responsible to an organization’s decision-making. Such processes can frequently develop strong leadership qualities as well. 

Finally, there is little doubt that analytics will play a significant role in enterprise in the future learning analytics in all aspects of life.

FAQs on IIM SKILLS vs. SRM University Data Analytics Course

Question 1) What kind of job posts are available in the data analytics field?

Answer: Data analytics various job posts, some of them are the following:

  • Operations analyst
  • System analyst
  • Senior business analyst
  • Associate analyst
  • Business intelligence analyst
  • Analytics data architect
  • Marketing analyst and strategist
  • Technology Information analyst

Question 2) What is a dashboard in data analytics?

Answer: A data analytics dashboard is a tool for multitasking, organizing, visualizing, analyzing, and tracking data. A data analytics dashboard’s ultimate goal is to make it easier for data analysts, decision-makers, and ordinary users to understand their data, get deeper insights, and make better data-driven decisions. 

Data analytics dashboards are classified into three types: operational, strategic, and analytical:

  • Operations: Operational analytics dashboards are associated with the progress of work and the present status of operations. Operational dashboards are frequently used to understand where issues exist and resolve the issue to go further into data.
  • Strategy: Strategic analytics dashboards display key performance information and data visualizations. The demonstrating straightforward trends monitors and comprehend decisions based on key performance pieces of information.
  • Data dashboards are intended to integrate and extract critical information from a wide range of data sources, services, and APIs. Visuals like charts, maps, figures, scatter diagrams, bar charts, and tables are used to compile all information in a cohesive manner. A company deals with different programmable dashboards for each section and each project. It allows a more granular monitoring system of extremely specific KPIs.
  • Analytical: Analytical dashboards place a premium on flexibility, allowing users to investigate data points in as many different ways as possible, using filters and comparisons to uncover hidden insights. Drill-downs, prediction models, and what-if parameters are all common aspects.

Question 3) What are some serious classifications of data analytics?

Answer: Data analytics is divided into four fundamental sorts or groups. While their focus and goals may differ, they are all steps toward analytical maturity, which is a measure of an organization’s capacity to extract value from relevant data. The four types are as follows:

Descriptive analytics

Descriptive analytics is concerned with describing historical data, whereas diagnostic analytics is concerned with determining the reason for a specific outcome or event in the past. It uses data to find trends that can help a business understand its product development process.

Predictive analytics

Predictive analytics employs data to forecast future outcomes or events to assist businesses in meeting their objectives. To accomplish this, data analysts frequently construct optimal simulation models to assist them in making accurate forecasts.

Diagnostic analytics

Diagnostic analytics is concerned with determining the reason for a specific outcome or event in the past. It employs data to detect trends that can help a firm learn about its most recent buyers and select and optimize its sales strategy.

Prescriptive analytics

The most advanced sort of data analytics is prescriptive analytics. It is comparable to predictive analytics in that it provides enterprises with valuable insight. It differs in that it focuses on advising the optimal course of action or solution based on predictive analytics. Prescriptive analytics frequently necessitates the use of machine learning algorithms and other sophisticated techniques. This means that in many circumstances, only firms with significant resources and an advanced analytics methodology can perform it.

IIM SKILLS vs. Ivy Professional School Data Analytics Course Review

by | Nov 2, 2024 | Courses, Data Analytics, Institute Review

Data analytics is one of the most competitive and high-paying jobs in the technical industry. Please read this article – Data Analytics IIM SKILLS vs. Ivy Professional School Data Analytics Course to get a better understanding of courses and institutions.

IIM SKILLS vs. Ivy Professional School Data Analytics Course

 

Data Analytics

Data analytics skills are known as observational skills in simple definition, in high demand as more companies aim to improve operations and drive results by using data to inform decision-making. Gain crucial data science competencies by taking a data business analytics online course and receiving a certificate of completion from any reputable institute.

As businesses generate more data in the digital age, the demand to analyze and interpret this quantitative information grows. Professionals with data-analytical abilities are invaluable because they can derive relevant insights from organized and unstructured data acquired by businesses. To succeed in this field, you must first master the principles of data analysis, such as how data is gathered, saved, and retrieved, how to interface with databases using Structured Query Language (SQL), and how to visualize data using applications such as Microsoft Excel or Tableau.

The primary advantage of data analytics is to use the data capacity in analytical models to appropriate business choices. A variety of businesses demands analytical skills as it is required in financial transactions, operation deals, promotion, and human resource management by company executives. Managers with data science credentials can influence change and success in the corporate world by harnessing actionable insights through analytics and conveying findings to stakeholders via visualization tools such as Tableau. As traditional business positions become more complicated and flexible, there is an increasing demand for people who can analyze data as well as convey results to drive corporate plans.

The usage of data and information technology (IT) expands helps and business and technological methods. Individuals in this sector, known as business systems analysts, can effectively bridge the gap between IT and leadership teams. The critical role in improving an organization’s function, and profitability by implementing more efficient authorizing change.

Learn how to harness the power of technology by taking a short online course in data analytics or business analytics. Gain up-to-date skills in data science and play a significant role in making data-driven decisions for your organization, whether you are an experienced data analyst or joining the profession for the first time.

How Do Data Analytics Help Types of Businesses?

Data analytics assists businesses in all elements of their operations, from sourcing supplies to estimating demand to accounting, human resource activities, and all aspects of marketing, among others.

Businesses are highly dependent on analytics to identify numbers in their operations. Furthermore, it provides thorough insights on what is and is not working on all aspects of business operations, such as marketing and sales scenarios such as content, social media campaigns, email marketing, website traffic, number of sales, and much more.

Data analysis gives significant value by providing the necessary knowledge to streamline corporate actions and results. To improve the outcomes of all of their business activities, a corporation can use analytics to better comprehend the following scenarios:

  • Making sense of useless corporate data
  • Highlight minor errors
  • Reduce customer service challenges
  • Make businesses proactive rather than reactive.
  • Urgency 
  • Getting rid of the unknown

Many businesses profit greatly from data analytics since data has become the lifeblood of an organization’s efficiency, and cloud computing services enable all possible data mining, data modeling, and data processing requirements. Let’s look at some of the top industries that are employing data analytics and exploiting data to drive future growth in their respective fields.

Use of Data Analytics in Industries

Banking and securities, government, media and entertainment, and a few other areas have seen a surge in demand for analytical solutions and tools.

Securities and Banking

Hedge funds, retail trade, and large banks in the banking and financial markets have all deployed big data technologies to monitor trade analytics used in high-frequency trading, sentiment measurement, pre-trade decision-support analytics, predictive analytics, and so on. Other hot areas that heavily rely on data and analytics solutions include risk analysis, anti-money laundering, KYC (know your customer), fraud reduction, and demand enterprise risk management.

Banking and security organizations monitor financial market movements utilizing data analytics techniques and solutions. 

Insurance Industry

To understand and manage their connections with clients regarding claims, underwriting, future consumer requirements, and much more, property and casualty insurance firms use telematics, agent interactions, customer contacts, smart homes, and even social media campaigns. Companies leverage data observation to attract new customers with improved customer service, allowing them to maximize revenue.

Manufacturing Sector

Manufacturing industries of various types, as well as natural resources such as oil, gas, minerals, metals, agricultural products, and so on, have generated a large amount of data during the previous few years. The data is not only massive but also complex and difficult to manage, making them an ideal target for data analytics. However, this set of data is currently unexplored.

Now, the sector is aggressively investing in predictive analytics technologies and embracing digitization to turn itself into a data-driven decision-making industry. Companies are ingesting and integrating various types of important data, such as geospatial data, text, graphical data, IoT data, and temporal data, into datasets to provide usable information.

Pharmaceuticals and Healthcare

Pharma and the healthcare sector are also investing in modern cloud technology and big data to improve medical services and consumer satisfaction through analytics. Wearable trackers and RPM (remote patient monitoring) are only two examples of advancements in the healthcare business; they also aid in determining whether patients are taking their meds and adhering to the treatment plan correctly.

Data accumulated over time provides clinicians with extensive information and helps medical practitioners with their patient’s well-being as well as actionable insights. 

Also Read,

Travel & Transportation

Transportation The transportation business has various unexplored big data prospects. Governments in various nations employ big data to better understand people’s needs, transform cities into smart cities with IoT, control traffic, optimize route planning and intelligent transportation systems, and manage congestion.

The business sector uses big data to provide a better customer experience during holidays, corporate meetings, and other stays, much as the government sector invested and improved data for day transportation. Logistics organizations are also employing data analytics to manage revenue, speed up operations, and gain a competitive advantage. The transportation industry is only now beginning to see widespread embrace of change.

Wholesale and Retail Industry

The retail and wholesale industries thrive on higher profits and better customer service. To stay ahead of the competition, retailers are adopting data analytics to deal with expanding big data to precisely anticipate customer needs and then deliver those needs. Analytics enables them to compete in a crowded market and stay ahead of the competition. Extraction of detailed insights from data analytics solutions allows them to keep their customers pleased and return to their stores. Retailers use data analytics in practically every facet of their operations, including:

  • Improve marketing by personalizing the customer experience.
  • Improve logistics and supply chain management.
  • Manage prices to increase sales.
  • Make use of retail data analytics.

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Final Opinion:

Data analytics provides the technologies and tools needed to create a big data world with organized and unstructured data collections. Companies can utilize these solutions to optimize efficiency and avoid resource and time waste by strengthening their decision-making capabilities using data-driven insights. Many others are following suit and transforming their businesses to become data-driven to achieve better and more sustainable results. 

Read further about two educational platforms in this article- IIM SKILLS vs. Ivy Professional School

 IIM SKILLS vs. Ivy Professional School Data Analytics Course

IIM SKILLS

IIM SKILLS conducts a wide range of educational courses for every kind of student, including beginners, graduates, technologists, and mid-level and senior-level professionals. It has a reputation as a leading educational institution of online professional skills courses, providing complete training to excel at work or establish a business. These courses cover a wide range of topics, combining theory and practice, and apply to a variety of occupations and sectors. The well-planned content assists pupils in developing their abilities and receiving the greatest teaching. They can transform their passions into lucrative and fulfilling professions by identifying and improving their skill set.

The Data Analysis course duration is a path that fills students with confidence and skills. It is laid out at IIM abilities to help you gain the necessary abilities as you progress through the courses of the Data Analysis course. Reinforcing these industry-relevant abilities will provide you an advantage over your competitors in finding lucrative career opportunities in the market.

Modules Covered

Excel: Basic and Advanced

  •  Excel Environment Formatting and Conditional Formatting Overview
  •  Sorting, Filtering, and Validation of Data
  •  Knowledge of Name Ranges
  •  Chart types explained: column and bar charts, line and area charts, pie charts, doughnut charts, scatter plots
  •  Formatting a graph
  •  Creating and personalizing sophisticated charts such as thermometer charts, waterfall charts, and population pyramids
  • Data Analysis with Pivot Tables – Using the row and column shelves, values, and filters
  •  Summary reports, advantages and disadvantages of data stacking and cross-tabulation
  •  Modify the aggregation kinds and summarization.
  •  Using pivot data to create groups and bins
  •  Calculated field concept, usage, and restrictions
  •  Various report layouts are available, including outline, condensed, and tabular formats.
  •  Grand totals and subtotals can be displayed and hidden.
  • Reports making

Visual Basic Application components and working pattern

  •  What Is Logic and What Is VBA?
  •  What Is VBA?
  •  Macro Recordings Overview, IDE
  • VBA Language Elements That Are Required
  •  Programming statements, variables and data types, keywords, and syntax
  •  Comments, Operators
  •  Range Objects in Action
  •  Structures for Programming and Control, Looping Structures, With-End with Bloc, Worksheet and Workbook Functions, Automatic Procedures, and Event
  •  VBA Objects and Memory Management
  • Communicating with Your Users: Basic Dialog Boxes and User Forms
  •  Using Add-ins and User Form Controls
  •  Using the User Interface to Access Your Macros
  •  Using VBA, retrieve data from an Access database in Excel.

SQL

  •  What is SQL – A Brief Overview Installing MS SQL Server on Windows OS
  • Use of Server Management Studio Overview
  •  Understanding fundamental database principles
  •  Statements to Insert, Update, and Delete
  •  Subsetting, Filters, and Sorting are all part of the Select statement. 
  •  Grouping and aggregation
  •  SQL Functions: Number, Text, Date, and so on
  •  SQL Keywords: top, distinct, null, and so on
  •  SQL Operators: Relational (both single and multi-valued), Logical Application of wildcard operators and wildcard characters, et cetera
  •  Understanding the Fundamentals of SSIS
  •  Packages: An Introduction
  •  Parameterization and Visualization
  •  Using SSRS to Create Visualizations

Power BI

  • Power BI Overview and Installation
  • When working on a project, introduce different options in the Power BI Desktop Task pipeline.
  • Power Query Conditional Columns
  • Query Editor allows you to clean and alter data.
  • Define data granularity
  • Merging and appending data
  • Introduction to DAX Calculated Tables, Columns, and Measures
  • Time Intelligence in DAX
  • DAX functions that are frequently used in real-time 
  • Power BI Reports Development
  • Working with Various Visuals/Charts
  • Report Formatting Options
  • To filter visualizations, use a slicer.
  • Utilizing Filters 
  • Custom Visuals from the Gallery can be downloaded and used.
  • Include an R or Python visual.
  • Use key performance indicators.

Python

  • Statistics Fundamentals
  •  Central tendencies measurements
  •  Variance measures
  •  Frequency measurements
  • Operations on Matrixes
  •  Calculus Derivatives and Integration Overview
  •  Maxima and minima
  •  The area behind the curvature
  •  Theoretical Optimization

Processing with NumPy (Numerical Python)

Pandas Data operations (Series & Data structures)

Tableau- Tableau product, measure and dimensions

Introduction of R for Data Science, Data exporting in various formats

Duration: Six months

Average Course Fee:  INR 49900 + Taxes.

Placement: 100% Job Support.

Study material access: Lifetime access to all live and recorded Sessions.

Tools Access:  Lifetime access to all the tools

Faculty support: Doubt clearing and direct guidance with the Faculty

Refund policy: Money back guarantee after dissatisfaction

Other Professional Courses from IIM SKILLS

Ivy Professional School

Ivy Professional School is a pioneer in the country’s big data analytics and data science training disciplines and is the official training partner of corporations such as Genpact, HSBC, eBay/PayPal, ICRA, ITC, Capgemini, Cognizant, etc. Ivy Professional School has consistently ranked among the top data science and analytics schools in the US for the last five years. The specialist instructors at Ivy Professional School are affiliated with major institutions such as ISI, IIMs, IITs, and prestigious US universities.

Since its beginning in 2007, IVY has trained over 10,000 people from 10 countries, fifty organizations, and one hundred colleges (including IIMs, IITs, and ISIs). Ivy recently completed three face-to-face classroom sessions for a large analytics organization.

Individual participants can make use of Ivy’s extensive course content on analytic technologies such as SAS, R, Hadoop, Big Data, SPSS, machine learning, and the new buzzword Data Visualization.

The course and curriculum are heavily industry-focused, ranging from basic to advanced levels. Doubts will never go unanswered in any class, and what students like the most about the faculty is how fully they help a person understand the principles. Students will get hands-on experience with real-world projects and case studies in data analytics utilizing Hadoop, Spark, Hive, and AWS.

Course Modules

Dashboard and Automation Learning with the use of Advanced Excel

  • MS Excel Basics, Cell Reference, Basic Functions, and Usage
  • Sorting, filtering, advanced filtering, subtotal pivot tables, and slicers are all available.
  • Goal Look for and solve various charts Graphs: When and how to utilize them
  • Conditional Formatting: Vlookup, Hlookup, Match, and Index
  • Error Handling, Worksheet & Workbook Reference
  • IF and Nested IF are logical operators and functions.
  • Validation of Data
  • Text Features
  • Controls for Forms
  • Dashboard
  • Industry Case Studies from Insurance, Sales, Marketing, and Web Analytics

SQL Queries and Database Management

  • Fundamentals of Databases
  • Efficient Relational and Create Database Models
  • Case Studies in Database Model Design
  • Data Handling Case Study Implementation
  • Importing and Exporting a Large Volume of Data into a Database
  • DDL, DML, DCL, and DQL SQL Statements
  • Merging, joining, sorting, indexing, co-related queries, and so forth are all examples of transactional SQL queries.
  • Exercises in Data Manipulation Using SQL Queries
  • Using SQL Statements to Create Database Models
  • Individual SQL Statement Handling Projects

Tableau

  • An Overview of Data Visualization
  • Introduction to Tableau Data Visualization
  • Tableau Fundamentals
  • Utilizing Sorting and Filters
  • Making Dual Axis and Combination Charts
  • Calculations in a Table
  • Overview of the Calculated Field
  • 4 Case Studies Using Retail, Airline, and Bank Data

Business analysis and statistics

  • Data formats, and Visual Representation
  • Index Numbers, Correlation, and Data Modeling
  • Central Tendency and Dispersion Measures
  • Time Series Analysis and Forecasting
  • Bayesian Probability Theory Probability Mathematical Expectation and Distribution
  • Sampling and Distribution of Sampling
  • Estimation Theory and Hypothesis Testing

R

  • Introduction to R Data Handling in R Analytics and Statistics Overview
  • Overview of Analytics and Statistics: String and Character Functions in R
  • Time Series Theory Overview Linear Regression in R Logistic Regression in R
  • Case Study Feature Engineering and Dimension Reduction, as well as Case Study Decision Trees

Python

  • Python Scientific Distribution Essentials
  • Python Data Manipulation and Visualization Introduction to Predictive Modeling
  • Linear Regression Modeling
  • Logistic Regression Modeling
  • Forecasting Time Series

Machine Learning

  • Decision Tree for Supervised Learning
  • Ensemble Learning: Supervised Learning
  • Analytics and Text Mining

Program Name: Data Analytics With Visualization Certification Course

Duration: 195 hours

Average Course Fee: INR 40,684 / (Inclusive of All Taxes)

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Frequently Asked Questions (FAQs) on IIM SKILLS vs. Ivy Professional School Data Analytics Course

Question 1) What exactly is Big Data Analytics?

Big Data analytics has become the backbone of huge industrial and commercial firms in making critical decisions based on data analysis results. Data analytics is simply the act of analyzing data to identify patterns and develop conclusions to make an essential choice. Nowadays, thanks to technological advancements, data may be evaluated utilizing advanced analytical approaches such as the analysis of structured, unstructured, and semi-structured data. Big data is a term used to describe large data sets that cannot be handled by traditional analysis databases. Data analysis has become a sought-after vocation by corporations and enterprises since it allows them to make faster, more efficient, and more intelligent judgments.

There are numerous career opportunities in the field of data analysis, but there are fewer people to fill them. Big data analytics is a booming area with an increasing number of enterprises and firms, but there are fewer people to fill these positions. As a result, firms are willing to pay top dollar to individuals with the necessary skill set in the field of big data analysis. The job of data analysis is not only limited to concluding for the company to make better decisions, but they can also take on other jobs such as machine learning, data architecture, and data modeling where they get to explore new algorithms and new aspects of data analysis.  

Question 2) Have in India and around the World any thriving Scope of Data Analytics? 

Answer:  Data analytics is surely in high demand because enterprises and large corporate firms require these analysts to help them make faster and more successful business decisions. The employment of new and advanced technologies in this industry demonstrates the importance of data analysis and processing in enterprises and firms. They are acquiring the greatest software and machines available to assist them in the processing and analysis of large amounts of data. Data analysis assists in making pricing strategy decisions, determining ways to cut various costs, and optimizing the procedures used by the business or firm to make the system in the business cost-efficient and effective.

Data analysis studies are not limited to just analyzing patterns to come up with effective solutions; rather, there are many jobs in computer-related skills as well, such as developing new software, retrieving data using machine language, and using machine learning to better understand the process of data analysis and data mining. The scope of data analysis is not restricted to a specific sector of corporations or enterprises; it is a skill that is necessary in all operational companies all over the world.

Question 3) What are some of the quintessential skills for Data Analytics?

Answer: Jobs in the field of data analytics necessitate strong analytical abilities as well as numerical abilities. To make effective and timely decisions, the individual must be able to think reasonably and critically. In addition to these, prospective candidates for big data analytics employment must possess particular technical skills. A candidate seeking a job in big data analytics should have the following characteristics:

  • Analytical abilities
  • Learning by machine
  • Java, Python, Scala, SQL, and MATLAB programming
  • Logical reasoning
  • Thinking critically
  • Decision-making abilities
  • Observational abilities

Concluding thoughts on IIM SKILLS vs. Ivy Professional School Data Analytics Course

We hope this extensive article on IIM SKILLS vs. Ivy Professional School Data Analytics Course has been able to answer some of your questions on data analytics and related courses, curriculum, duration, practical assignments among other things. Deep dive into the world of analytics and make a prosperous career for yourself. All the very best for the future!

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