Data Analytics For Professionals
Atul HarshaSenior Manager Content
In the digital age, data is the cornerstone of decision-making. The surge in data analytics jobs and the promising data analytics career path have led many individuals to explore this burgeoning field. Enrolling in a data analytics online course is a step towards gaining expertise and understanding the nuances of this domain.
- Understanding Data Analytics
- Latest Statistics and Data Analytics Trends for 2023
- How to become a Data Analyst?
- What Skillsets are required to become a Data Analyst in 2024?
- Career Path of a Data Analyst
- Who can Enroll? Data Analytics Online Course Eligibility Criteria
- Data Analytics Online Course
- Data Analytics Syllabus
- Top Companies Hiring Data Analytics Professionals
Understanding Data Analytics
Data analytics involves examining raw data to draw conclusions and insights. It's a subset of business analytics, focusing on processing and interpreting complex datasets to inform business decisions. Tools like NVivo and KNIME are often used for managing and analyzing data.
Latest Statistics and Data Analytics Trends for 2023
- The global market for data analytics is expected to be worth over $100 billion in 2023.
- The analytics market size is seen to grow to a $57 million industry by 2023.
- 91.9% of organizations achieved measurable value from data and analytics investments in 2023.
- More businesses will operationalize AI, and analytics will become more pervasive, democratized, and composable in 2023.
- The big data analytics market is set to reach $103 billion by 2023
- Investors have poured in $43.8 billion in 1,300 big data analytics companies as of February 2023
- Poor data quality costs the US economy up to $3.1 trillion
- The big data analytics market soared by 62%, from $169 billion in 2018 to $274 billion in 2022, and is anticipated to create $103 billion by 2027
How to become a Data Analyst?
Becoming a data analyst requires a combination of education, skills acquisition, and practical experience. Below is a step-by-step guide on how to become a data analyst:
| Category | Action Items | Details |
|---|---|---|
| Educational Background | A. Obtain a Bachelor’s Degree | - Opt for degrees in Statistics, Mathematics, Information Technology, or Business. |
| B. Take Relevant Courses | - Focus on courses in statistics, mathematics, computer science, and business. | |
| Technical Skill Development | A. Learn Programming Languages | - Become proficient in Python or R. |
| B. Master Database Management | - Learn SQL for effective database management. | |
| C. Learn Data Visualization Tools | - Familiarize with tools like Tableau or PowerBI. | |
| Knowledge in Data Analytics | A. Enroll in Online Courses and Certifications | - Choose platforms like Coursera, edX, or Udemy. |
| B. Understand Data Processing | - Learn about data cleaning, transformation, and processing. | |
| Practical Experience | A. Work on Real Projects | - Engage in real-world data analytics projects. |
| B. Create a Portfolio | - Showcase your data analytics projects and skills. | |
| Job Application Process | A. Prepare Resume and Cover Letter | - Highlight skills, education, and experience. |
| B. Apply for Entry-Level Positions or Internships | - Target relevant data analyst positions. | |
| Continuous Learning & Networking | A. Pursue Advanced Degrees or Certifications | - Consider further education in data analytics or related fields. |
| B. Join Data Analytics Forums and Groups | - Network with professionals and stay updated on industry trends. | |
| Career Advancement | A. Gain Experience in the Field | - Work in various roles to accumulate experience. |
| B. Continuously Update Skills | - Learn about the latest tools, technologies, and best practices in data analytics. |
This tabular guide provides a clear and organized pathway for aspiring data analysts. Following these steps, continuously learning, and adapting to new trends and technologies in the field will help individuals successfully establish a career in data analytics.
What Skillsets are required to become a Data Analyst in 2024?
| Skill | Description | Real-Life Application |
|---|---|---|
| 1. Statistical Knowledge | Understanding of statistical concepts and methodologies. | - Conducting hypothesis testing to validate assumptions and make informed decisions. - Utilizing probability distributions to model uncertain events in data analysis. |
| 2. Programming Skills | Proficiency in languages like Python or R for data manipulation and analysis. | - Using Python to automate the collection and cleaning of data from multiple sources. - Employing R for advanced statistical analysis and data visualization. |
| 3. SQL Expertise | Ability to write and execute complex SQL queries for database management. | - Writing SQL queries to join multiple tables from a database, providing a comprehensive dataset for analysis. - Utilizing SQL for data filtering and sorting to facilitate efficient analysis. |
| 4. Data Visualization | Capability to create clear, insightful visual representations of data. | - Creating interactive dashboards using Tableau to present data insights to stakeholders. - Designing clear and concise data visualizations to represent complex data trends and patterns. |
| 5. Data Cleaning | Skills to clean and organize raw data into a usable format. | - Employing data cleaning techniques to handle missing or inconsistent data, ensuring the reliability of the dataset for analysis. - Using data transformation methods to normalize and standardize data. |
| 6. Problem-Solving Ability | Capacity to approach and solve complex issues analytically. | - Identifying the root cause of data discrepancies and developing strategies to address them. - Analyzing large datasets to uncover hidden patterns and insights to solve business problems. |
| 7. Machine Learning Knowledge | Understanding of machine learning algorithms and their application. | - Implementing machine learning algorithms to develop predictive models for customer behavior. - Utilizing machine learning to automate the classification and segmentation of data. |
| 8. Business Acumen | Insight into business operations and strategies. | - Analyzing sales and customer data to provide actionable insights for marketing strategies. - Utilizing data analysis to optimize supply chain operations and improve business efficiency. |
Career Path of a Data Analyst
This is a career path for someone who wants to start their journey as a data analyst in 2024. It considers the evolving trends in data analytics, the increasing integration of AI and machine learning, and the continuous demand for advanced analytical skills.
| Year | Position | Responsibilities | Skills and Tools |
|---|---|---|---|
| 2024 | Entry-Level Data Analyst | - Collecting and interpreting data - Analyzing results - Reporting the results back to relevant teams | - Excel, Basic SQL, Basic Statistical Analysis, Data Visualization Tools (e.g., Tableau) |
| 2026 | Intermediate Data Analyst | - Mining data from primary and secondary sources - Cleaning and pruning data - Analyzing and visualizing data | - Advanced SQL, Python/R, Data Cleaning Tools (e.g., Trifacta), Advanced Data Visualization |
| 2029 | Senior Data Analyst | - Designing and maintaining data systems and databases - Troubleshooting data-related problems and authoring reports | - Machine Learning Algorithms, Advanced Analytics Tools (e.g., SAS, Apache Hadoop), ETL Tools (e.g., Talend) |
| 2032 | Data Scientist | - Creating advanced analytics models - Utilizing machine learning and AI to analyze data | - Advanced Machine Learning, AI Integration, Big Data Tools (e.g., Spark, Hive), Cloud Platforms (e.g., AWS, Azure) |
| 2035 | Data Analytics Manager | - Overseeing analytics teams - Developing strategies for data analysis and reporting | - Leadership Skills, Project Management Tools (e.g., Jira), Data Governance, Strategic Planning |
| 2039 | Director of Data Analytics | - Directing and organizing the analytics department - Ensuring data accuracy and usability | - Strategic Thinking, Organizational Skills, Change Management, Advanced Data Strategy |
| 2044 | Chief Data Officer (CDO) | - Overseeing the organization's data and analytics strategy - Ensuring data governance and compliance | - Executive Leadership, Policy Knowledge, Risk Management, Corporate Strategy |
Note:
- The above table outlines a potential career progression for a data analyst starting in 2024. The years are indicative and represent the time spent in each role, which may vary for different individuals.
- Continuous learning and upskilling are crucial at every step to stay abreast of the latest trends and technologies in the data analytics domain.
- Additional certifications and qualifications in relevant areas will further enhance career progression opportunities.
Who can Enroll? Data Analytics Online Course Eligibility Criteria
| Who Can Enroll? | Background | Objective |
|---|---|---|
| 1. Students | - Students from various fields including Statistics, Mathematics, Computer Science, Information Technology, and Business. | - To gain foundational and advanced knowledge in data analytics. - Enhance future career prospects and prepare for data analytics roles. |
| 2. Working Professionals | - Professionals from sectors like IT, Finance, Marketing, and Healthcare. | - To upskill and transition into data analytics roles. - Leverage data analytics for better decision-making in their current roles. |
| 3. Entrepreneurs/Business Owners | - Individuals who own or manage a business. | - To understand and utilize data analytics for improving business decision-making and strategies. |
| 4. Career Changers | - Individuals from diverse professional backgrounds seeking a career shift. | - To acquire the necessary skills and knowledge for a successful career in data analytics. |
| 5. Freelancers | - Independent professionals offering various services. | - To add data analytics to their skill set and provide additional services to clients. |
Data Analytics Online Course
Online data analytics courses are ideal for working professionals who wish to learn data analytics along with their day-to-day job.
| Course Name | Skills You'll Gain | Rating | Level | Duration |
|---|---|---|---|---|
| Google Data Analytics | Data Analysis, Data Management, Business Analysis, SQL, Spreadsheet Software, Data Analysis Software, Data Visualization, Databases, Critical Thinking, Data Structures, Problem Solving, Programming Principles, and more. | 4.8 (127.7k reviews) | Beginner | 3 - 6 Months |
| IBM Data Analyst | Data Analysis, Python Programming, Data Visualization, Computer Programming, Data Management, Statistical Programming, Exploratory Data Analysis, Data Analysis Software, Statistical Analysis, Data Structures, Basic Descriptive Statistics, and more. | 4.6 (69.3k reviews) | Beginner | 3 - 6 Months |
| Introduction to Data Analytics | Data Analysis, Data Management, Big Data, Basic Descriptive Statistics, Data Visualization, Databases, Python Programming, Cloud Computing, Data Mining, Machine Learning, Data Science, Microsoft Excel. | 4.8 (12.8k reviews) | Beginner | 1 - 3 Months |
| Google Advanced Data Analytics | Communication, Computer Programming, Data Analysis, Exploratory Data Analysis, General Statistics, Machine Learning, Probability Distribution, Project Management, Python Programming, Regression, Statistical Analysis, Tableau Software. | 4.7 (1.7k reviews) | Advanced | 3 - 6 Months |
| Business Analytics with Excel: Elementary to Advanced | Business Analysis, Data Analysis, Data Visualization, Spreadsheet Software, Data Model, Decision Making, Microsoft Excel, Process Analysis, Statistical Visualization. | 4.7 (739 reviews) | Intermediate | 1 - 3 Months |
Data Analytics Syllabus
A data analytics course consists of the following topics:
| Syllabus of Data Analytics | ||
|---|---|---|
| Data Structures and Algorithms |
Probability and Statistics |
Relational Database Management Systems |
| Business Fundamentals |
Text Analytics |
Data Collection |
| Data Visualization |
Statistical Analysis |
Forecasting Analytics |
| Simulation |
Machine Learning |
Optimization |
| Marketing Analytics |
Pricing Analytics |
Social Network Analysis |
| Retail Analytics |
Customer Analytics |
Supply Chain Analytics |
Some of the software tools taught in the course are:
| R |
Power BI |
| MySQL |
MongoDB |
| Hadoop |
Tableau |
| Python |
Excel |
| SAS |
Scala |
Check out data analytics interview questions to ace the interview round
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Top Companies Hiring Data Analytics Professionals
In today’s world, Data Analytics is the need of the hour. If a business enterprise has to excel in its field, it has to take the help of data analysis and data science. With the help of data analytics companies can not only increase their revenue, expand the customer base, provide better customer satisfaction, cut cost, but also get an edge over their competitors.
Data Analysts are the most sought-after skilled professionals in the current world, not only in the Information Technology industry but also in Finance, Insurance, Banking, Marketing and sales, Consumer Goods, Electronics, Heavy Industries and all other sectors; as all of them require someone to do the number crunching for them.
| Companies Hiring Data Analytics Graduates | ||
|---|---|---|
| |
MachinePulse |
The Smart Cube |
| Fractal |
Amazon |
Novartis |
| Fractal Analytics |
JP Morgan Chase |
Capital One |
| RBS |
ICICI Bank |
Flipkart |
| Kotak Mahindra |
Accenture Consulting |
KPMG |
| Yahoo |
|
Tumblr |
| Tredence |
Cartesian Consulting |
Quantium Analytics |
| Deloitte |
HSBC |
Credit Suisse |
| Barclays |
Axis Bank |
E-bay |
| Expedia |
AT Kearney |
CRISIL |
| Microsoft |
|
Mu Sigma |
| BRIDGEi2i |
Flytxt |
Tata iQ |
| Citi Bank |
Deutsche Bank |
Nomura |
| HDFC Bank |
Yes Bank |
Snapdeal |
| Make My Trip |
E&Y |
Walmart Labs |
| |
|
ZS Associates |
| Brillio |
Bank of America |
- |
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Student Forum
Anything you would want to ask experts?Answered Yesterday
The PGDM in Data Analytics at IILM College is a comprehensive two-year programme designed to equip students with the skills needed to excel in the field of data analytics.Here are some key aspects:
Academic Excellence
The curriculum is academically rigorous and research-supported, ensuring a strong
A
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Contributor-Level 10
Answered 5 days ago
Adani Institute of Digital Technology Management (AIDTM) also offers an Executive Program in Business Analytics (EPBA). This one-year programme is delivered by industry and academic experts and is designed to minimize disruption to working professionals.
The PGDM in Big Data Analytics programme at A
Guide-Level 13
Answered a week ago
NIT Andhrapradesh offers eight specialisations in M.Tech courses. In addition, the institute offers around 90 seats for all its M.Tech courses, and 15 seats are offered in M.Tech in Computer Science and Data Analytics. For NIT Andhra Pradesh M.Tech admissions, candidates are required to qualify for
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Contributor-Level 8
Answered 4 weeks ago
Absolutely yes, SASTRA Chennai Campus is good for M.Sc in Artificial Intelligence and Data Sciences .
This institute have a good record of quality education. Faculty members are well qualified and experienced & most of them are Ph.D scholars so they have good knowledge of their subjects.Infrastructu
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Beginner-Level 5
Answered 2 months ago
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Answered 2 months ago
A Master of Science in Business Analytics at the University of Texas at Dallas offers students practical and theoretical knowledge in a variety of fields like Data Science, Data Engineering, and Data Analytics. The programme allows the students to opt for either a flex, cohort or Online degree optio
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Contributor-Level 10
Answered 2 months ago
Indeed, pursuing an MBA in Data Analytics from Best Business School In Bangalore GIBS is beneficial. This is the reason why:
Career Growth: Graduates are well-suited for leadership positions in data analytics since it blends business management with data-driven decision-making.
High Demand: The need f
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Contributor-Level 9
Answered 2 months ago
An MBA in Data Analytics graduate's pay may differ according to region, industry, and level of expertise. Graduates from GIBS and affiliated universities can typically anticipate the following:
Entry-Level: In countries like the United States, United Kingdom, or Australia, recent graduates can begin
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Contributor-Level 9
Answered 2 months ago
To be eligible for an MBA in Data Analytics through Top best business school GIBS and partnering universities like the University of Northampton, candidates generally need to meet the following criteria:
Bachelor’s Degree: A recognised undergraduate degree in any discipline, though a background in bu
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Contributor-Level 9
Answered 2 months ago
Like any graduate program, a Master's in Data Analytics can be challenging requiring dedication and effort. The difficulty often depends on your background in quantitative subjects and your willingness to engage with the material. However, many find it rewarding and manageable with the right prepara
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Contributor-Level 10
Answered 2 months ago
While coding is helpful especially in advanced data analytics roles, it is not always necessary. Many tools (like Excel, Tableau, and others) allow you to perform data analysis without extensive coding knowledge.
P
Contributor-Level 10
Answered 2 months ago
Graduates typically analyze data to derive insights, inform strategic decisions and drive business improvements. They may work in roles such as data analysts, business analysts or managers overseeing analytics projects.
P
Contributor-Level 10
Answered 2 months ago
An MBA in Data Analytics focuses specifically on data analysis, statistical methods and data-driven decision-making while a general MBA covers broader business concepts without a specific emphasis on data. The specialised programme prepares graduates for the roles that requires strong analytical ski
P
Contributor-Level 10
Answered 2 months ago
Graduates can find opportunities in a wide range of industries including:
- Finance
- Healthcare
- E-commerce
- Consulting
- Technology
- Retail
P
Contributor-Level 10
Answered 2 months ago
An MBA in Data Analytics equips you with both technical and managerial skills enhancing your ability to interpret data and make strategic decisions. This combination prepares you for leadership roles increases your employability and positions you for promotions in data-driven organizations.
P
Contributor-Level 10
Answered 2 months ago
While a background in coding can be beneficial, it is not strictly necessary. Many programs are designed to accommodate students from various backgrounds. Basic familiarity with data analysis tools and concepts is helpful but most courses provide foundational knowledge in analytics tools and program
P
Contributor-Level 10
Answered 2 months ago
Yes, several reputable institutions offer specialised MBA programs in Pharmaceutical Management, including:
P
Contributor-Level 10
Answered 2 months ago
The average GMAT score of MSU admitted Class of 2023 of MSc in Business Data Science & Analytics was 693. The entry requirements are given below:
- A 4-year’s bachelor’s degree
- GMAT / GRE score
- Two Letters of Recommendation
- Personal Statement
- Resume
- Video essay
- Academic transcripts
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Contributor-Level 10
Answered 2 months ago
Michigan State University MSc Business Data Science & Analytics course is a STEM-certified degree course. This graduate course at the university focuses on business strategy, data tools and management, and experiential project consulting. This course’s graduates have gone on to become Data Analysts
Contributor-Level 10
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