IIM Skills vs Praxis Business School Data Analytics Course Review
Want to learn more about data and become a data analyst? Intending to move on with data analysis? If a candidate wants to work as a professional data analyst, they must possess a solid understanding of the procedures and instruments used to assess data. This article IIM SKILLS vs Praxis Business School Data Analytics Course includes a list of the top institutions that offer courses in data analytics. Please start reading this post as we’ve offered the first career steppingstone if you’re interested in joining this growing industry but aren’t sure where to start.
But first of all, let us begin to understand data analytics.
Data Analytics: What is It?
Analytics of data. What is it exactly?
Data analytics, to put it simply, is a methodical strategy for making decisions. It seems to be quite straightforward! The truth is that a “scientific approach” requires an awareness of a wide range of details in relation to data gathering, cleaning, and analysis.
Why is Data Analytics Currently a Big Deal?
Since the first time that humans scratched numbers onto wax tablets, data analytics has existed in some form. But data analytics didn’t start to take off in the contemporary sense until the dawn of the digital age.
This is primarily due to the enormous volumes of data that we now generate daily, whether we’re taking an Uber, transferring money, or simply composing an email.
As data has increased, so have the tools that automate a sizable portion of data analytics. This uses advanced data storage systems and machine learning algorithms, both of which make handling enormous volumes of data fairly straightforward.
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The Characteristics of Data Analysis:
Although data analysis encompasses a wide range of characteristics, the following are some typical ones:
A multitude of factors, such as volume, velocity, and variety, have an impact on them.
Now let’s look at the characteristics of data analysis that make it unique compared to other traditional methods of analysis.
Programmatic:
Due to the volume of data, it may be essential to create a program for data analysis that utilizes code to alter the data or carry out any type of research.
Data-driven:
Many data scientists rely on a hypothesis-driven strategy when they analyze data. One can also access the data to support analysis for proper data analysis. When there is a vast volume of data, this can be a huge advantage. Machine learning techniques, for instance, can be utilized in place of hypothetical analysis.
Use of Attributes:
There are numerous features that can be used for proper and accurate data analysis. In the past, analysts worked with the data source’s hundreds of qualities and features. There are now millions of observations and thousands of attributes thanks to big data.
Iterative:
Data analytics can be iterative in nature because the total data is divided into samples, which are then examined. The models can be improved through iteration until the data analysts are happy. New programs created to address analysis requirements and time constraints have resulted from this.
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What Are the Difficulties Faced by Data Analytics?
Not convinced despite data analytics’ benefits and optimism. But it’s easier said than done to get these advantages. Risk managers may encounter a number of difficulties when gathering and applying analytics.
Data Privacy and Security:
Data privacy refers to the appropriate use, collection, retention, deletion, and storage of data whereas the policies, procedures, and equipment used to safeguard private data are referred to as data security.
In order to safeguard your information, you need to ensure that it is secure. Otherwise, unauthorized access to your data can expose you to various cybersecurity risks.
Data Quality:
In order to determine data quality, a dataset must meet standards for accuracy, completeness, validity, consistency, uniqueness, timeliness, and suitability for the purpose for which it was intended.
Scalability:
Scalability is the capacity of a system, network, piece of software, or organization to expand and competently handle growing demands. When a network’s infrastructure is scalable, it may be expanded to accommodate more computers or servers as the workload grows. In short, a large dataset can be analyzed efficiently with the right techniques and infrastructure when it comes to large datasets.
Interpreting Results:
The process of evaluating data and drawing pertinent conclusions from it using different analytical research techniques is known as data interpretation. With the help of data analysis researchers can categorize, manipulate, and summarize data to find answers to important issues. Domain knowledge is necessary for data analysis to yield relevant results.
Difference Between Data Science and Data Analytics?
How can organizations improve decision-making, increase efficiency, and boost profitability using data analytics and data science? You must first understand the two terms in order to recognize their differences. So, let’s begin by discussing data science.
Data scientists use programming, math, and statistics to drive organizational strategy, master machine learning, models, and algorithms, and collaborate with sales, marketing, and business leaders.
Data analytics is a method for increasing effectiveness and achieving success in business. Data sets are evaluated to make inferences about the information they hold. Information is extracted, categorized, and evaluated to identify and assess conduct information. Various approaches are available depending on the needs of the company. Analyzing data was another name for it.
Thus, both data management and analysis as well as data analytics involve the procedures, techniques, and instruments for gathering, arranging, and storing data. The main goal of data analytics is to use technology and statistical analysis to examine data in order to identify trends and develop solutions. Analytics also gives companies the ability to react swiftly to changing market trends and gain an advantage over competitors. The improvement of company performance is the main objective of data analysis.
Well, if you are not familiar with the real world of data, then both the terms “data analytics” and “data science” will certainly be utilized. Although these terms are very similar in meanings, they are used to describe different topics.
Businesses must find professionals who can sort through the volume of data, analyze it, and help them make wise decisions as the amount of data is growing explosively.
Today, we examine some of the best online course providers in greater detail to see how they stack up against one another and how they might assist students in beginning a career in data analytics.
IIM SKILLS vs Praxis Business School Data Analytics Course – Overview of the Institutes
IIM SKILLS is a reputable online learning portal providing several courses in finance, marketing, writing, financial modelling, technical writing courses etc. Their data analytics course offers carefully crafted course structures that support the enhancement of fundamental knowledge and the development of the necessary skills, which benefits many people who want to pursue jobs in the field of data analytics. The institute was founded by Vaibhav Kakkar in the year 2015.
IIM SKILLS provides certification from Government recognized Master Certification in Data Analytics Course.
The IIM SKILLS Data Analytics Course offers a top-notch curriculum which is quite extensive, current, and relevant. It is periodically updated to reflect all new developments in the topics. It includes all the necessary elements needed to excel in your career. Paid internships that give you a sense of how things operate in the real world serve as a way to put your knowledge to the test.
IIM SKILLS: The Special Features of This Course Are as Follows:
- The course materials contain more than 10 case studies and 7 real-world projects with renowned industries.
- It provides 160 hours of lecture and 100 + hours of practical assignments.
- Students may enroll in the institute’s 2-month internship program when the course is completed. The students gain hands-on experience with all the knowledge they have gained in class, as well as help overcoming challenges and problem-solving skills.
- 24*7 support to students
- Students have the opportunity to interact live with mentors and trainers with extensive industrial experience.
- The students have access to the Learning Management System (LMS) which houses all of the taught content ,video recordings, and all other materials for the whole lifetime .
- The participants are also provided with free demo class.
- The institute provides assistance with resume-building and comprehensive placement support.
- 100% guaranteed placement.
All topics pertaining to data analytics and careers as professional data analysts are covered in great detail in the IIM Skills data analytics course. You develop expertise in several fields, such as clustering, DBScan, NumPy, and Python Libraries, among many others.
Furthermore, you learn how to use interactive dashboards and grow more accustomed to visualization tools. The course covers all four types of maps: Heatmap, Pareto, Waterfall, and Tree. With the use of live interactive sessions, IIM SKILLS’ data analytics course adopts an immersive learning strategy.
Its post-course support is one of its distinguishing features. It is significant that IIM Skill supports its students long after they have completed their studies.
Their professors are really excellent and remarkable. They are dedicated educators with a wealth of experience and degrees who provide their pupils the best of what they know while also assisting them in advancing their careers.
Consequently, it can be said that IIM Skills is one of the best institutions, having educated more than 35000 students. IIM Skills provides adequate student support, including problem-solving, academic counseling, soft skills training, resume preparation, placement assurances, internships, and other varied career advancement services.
IIM Skills has a very reasonable fee structure that guarantees that everyone who is interested in enrolling in a course will have access to all the facilities they are able to offer. Participants are also given the option to get a refund after the first class if they are dissatisfied.
IIM SKILLS employs a 360-degree pedagogy, fostering student confidence and expertise through immersive learning experiences, virtual sessions, practical projects, and special classes for complex modules.
To assist students in getting placed in corporate companies based on their knowledge and abilities, IIM SKILLS has worked with 350+ top-tier brands, including Cisco, Amazon, Swiggy, and many others. More than 35000 successful career changes can be attributed to them.
Other Professional Courses from IIM SKILLS
- 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
Now, let’s talk about Praxis Business School
Praxis Business Schools is a notable institution, that offers business analytics and data analytics courses. It is headquartered in Kolkata, India, and esteemed for its academic program, faculty, resources, and placement success rates. It was founded by Charanpreet Singh in 2007 and is a prestigious business school. It is situated in the southern outskirts of Kolkata. The institute has been approved by the AICTE, the All-India Council for Technical Education.
The following are some explanations as to why Praxis Business School might be regarded as one of the best colleges for data analytics:
Praxis Business School provides a comprehensive curriculum in data analytics, encompassing statistical analysis, data visualization, machine learning, big data analytics, and predictive modeling for real-world applications. Their curriculum is a perfect amalgamation of both experimental and theoretical learning which in my opinion is crucial in the modern world.
It boasts a faculty with extensive data analytics expertise, providing students with up-to-date industry trends and best practices.
The School offers a practical, industry-oriented approach to data analytics education, incorporating case studies, real-world projects, and internships to prepare students for real-world business problems.
Praxis Business School boasts modern classrooms, computer labs, and data analytics labs, ensuring students have access to the necessary resources and tools for effective data analytics learning.
It excels in data analytics placements, leveraging strong connections with various companies and organizations to secure internships and job opportunities for students.
For students with both programming and non-programming backgrounds, Praxis Business School’s Data Science program is excellent. The college provides a 9-Month Full-Time Program in Data Science, which is ranked #2 out of all Data Science programs nationwide.
The college’s faculty is approachable and helpful, making students feel comfortable with the subject. Since the curriculum includes both theoretical and experiential learning, it helps in making students industry ready. The program targets those serious about a career in analytics, regardless of prior experience in Data Science.
The college offers remarkable placement assistance, with renowned companies like Applied Research Works, Bridgei2i Analytics Solutions, Hinduja Global Solutions, Fractal Analytics, HSBC Analytics, and ICICI Bank recruiting students. The average salary ranges from Rs. 9.82 lakhs to Rs. 22.1 lakhs.
Comparison of IIM Skills vs Praxis Business Schools Data Analytics Courses: Duration of the Course
| IIM Skills | Praxis Business Schools |
| They offer a 6-month course duration | Praxis PGP course is offered for a duration of full-time 9-months in Data Science and Data Engineering. |
Comparison of IIM Skills vs Praxis Business Schools Data Analytics Courses: Eligibility Criteria
| IIM Skills | Praxis Business Schools |
| IIM SKILLS has very few, if any, pre-requisite requirements in order to be enrolled into the course. Anyone can begin from scratch to enter this cutting-edge sector if they are deeply interested in and fascinated by data analytics. The basic eligibility criteria are as follows:
| The eligibility criteria for PGPDE (Post Graduate Program in Data Engineering)
The Eligibility criteria for PGPDS(Post Graduate Program in Data Science)
|
Comparison of IIM Skills vs Praxis Business Schools Data Analytics Courses: Selection Criteria
| IIM Skills | Praxis Business Schools |
Selection Criteria for this course is based upon candidates who are:
| Selection Criteria for PGP in Data Science
|
Comparison of IIM Skills vs Praxis Business Schools Data Analytics Courses: Fee Structure
| IIM Skills | Praxis Business Schools |
| The course fee is INR 49900 + taxes | The course fees for the Post Graduate Program are divided into 2 fields: INR 1,500 (PGPDS)-Post graduate Program in Data Science |
Comparison of IIM Skills vs Praxis Business Schools Data Analytics Courses: Contact Information
| IIM Skills | Praxis Business Solutions |
| [email protected] 9580740740 | https://praxis.ac.in/ 7676160161 |
Comparison of IIM Skills vs Praxis Business Schools Data Analytics Courses: Course Modules
In IIM Skills the course modules are like this:
Modules | Topics Covered | |
| 1) | Data Analytics Using Advance Excel (9 hrs.) | Introduction to Data Handling Data Visualization in Excel Data Manipulation Using Functions Data Analysis and Reporting Overview of Dashboards Create Dashboards in Excel- Using Pivot Controls |
| 2) | Data Analytics Using VBA (15 hrs.) | Introducing VBA Key Components of Programming Language How VBA Works With Excel Programming Constructs in VBA Procedures and Functions in VBA – Modularizing Your Programs Objects and Memory Management in VBA Communicating With Your Users Others |
| 3) | Data Analytics Using SQL (39 hrs.) | Basics RDBMS Concepts Utilizing the Object Explorer Data Based Objects Creation (DDL Commands) Data Manipulation (DML Commands) SQL Server Reporting Services SQL Server Integration Services Other |
| 4) | Data Analytics Using Power BI (24 hrs.) | Introduction Data Preparation and Modelling Keep and Remove Rows, Go to Columns, and Add, Remove Data Analysis Expressions (DAX) Reports Developments (Visuals in Power BI) |
| 5) | Data Analytics Using Python-I (10 hrs) | Introduction to Basic Statistics Introduction to Mathematical Foundations Introduction to Analytics and Data Science Python Essentials (Core) Operations With NumPy (Numerical Python) Overview of Pandas Cleansing Data with Python |
| 6) | Data Analytics Using Python-II (10 hrs.) | Data Analysis Using Python Basic Visualization Tools Visualizing Geospatial Data Data Visualization with Python Advanced Visualization Tools Statistical Methods and Hypothesis Testing |
| 7) | Data Analytics Using Tableau (15 hrs.) | Getting Started Data Handling and Summaries – I Data Handling and Summaries – II Building Advanced Reports/ Maps Table Calculations Calculated Fields |
| 8) | R for Data Science (20 hrs.) | Data Importing/Exporting Data Manipulation Data Analysis Data Visualization with R Using R with Databases Introduction to Statistics Linear Regression: Solving Regression Problems Testing |
| 9) | Data Analytics Using Alteryx(18 hrs.) | Data Analytics Using Alteryx |
However, in Praxis Business Schools the 9 months course has been divided into 3 trimesters. Their course modules are in the following manner
| Trimester 1 | Fundamentals of Python Mathematics for Machine Learning Introduction to Machine Learning Fundamentals of Statistics Market Research RDBMS and Data Warehousing Data Visualisation and Story Telling Data Security and Privacy |
| Trimester 2 | Advanced machine Learning Multivariate Statistics and Econometrics Time Series forecasting Big Data & loT with NoSQL and Spark Text Analytics Introduction to R Marketing Analytics Analytics in Finance |
| Trimester 3 | Fundamentals of Deep Learning Applied AI &Model Interpretation Data Engineering & Model Deployment SAS Workshop Health Analytics Agriculture Analytics Capstone Project |
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Frequently Asked Questions Related to IIM SKILLS Vs Praxis Business Schools:
Q1. What kinds of data points are necessary for analysis, and how might companies start gathering them?
Data is the most crucial component of any analytics project; therefore the firm must make sure it has a comprehensive understanding of both its customer and business data. For the proper data to be gathered in the right format, a long-term and short-term data strategy is required. The goals and tactics for this strategy vary depending on the type of business (e.g., research product or customer selling strategies, customer journey, etc.). Our ability to retain and present these data points in an intelligible manner depends on the technological infrastructure and data collection techniques that we develop.
Q2. Are dashboards the ideal way to introduce analytics?
Well, in most instances, Yes.
A dashboard, such as one made using Microsoft Power BI with some visualisations and correlation plots, was the first step in the analytics journey for the vast majority of the businesses we work with. In this manner, stakeholders can fully comprehend the data collected and any holes that need to be filled can be quickly found.
Additionally, it offers a solid platform from which to develop predictive analytics.
Q3. What volume of data is required for analytics?
For any analytics effort, data is the most crucial resource. Therefore, businesses must gather as much organized business, transactional, and consumer data as possible.
The best method, in our experience, is to conduct a data discovery workshop to determine the quantity and quality of the data you now possess, the location of its storage, and the crucial business questions you seek their resolution to.
After the workshop, we can offer advice regarding the effectiveness and usefulness of the data.
Conclusion to IIM SKILLS vs Praxis Business School Data Analytics Course:
Well, that brings a close to my blog. Hope that this blog will assist you in making an informed decision when selecting a college or institute where you may learn data analytics.
All of the pertinent material for both institutes has been covered. To make a wise choice, it would still be preferable to consult audience feedback and testimonials from previous participants.
The information presented above enables you to get ready for this new data-driven future and promotes the growth of a fundamental knowledge of data science.
