A Guide To Data Analytics Course by KPMG
Data helps businesses to interpret new and actionable insights, which helps managers make better decisions. Data analysts are now in huge demand and managers even without a technical background can raise their salaries by an average of 25% by learning these skills. But with so many contesting courses and boot camps available around online as well as provided by institutes, it can be tiresome for some people to know where to start looking. In this article, we will learn about Data Analytics Course by KPMG as the top learning platform that will help you gain expertise and become a certified Data Analyst.
What is Data Analytics?
Data analytics is the gathering, modification, and organization of data to deduce, make predictions and drive informed decision-making by organizations for their benefit. Data analysts are needed to interpret millions of data to help companies make better decisions about their services and strategies.
Data analytics techniques can reveal patterns and trends that would create a bigger picture that would otherwise be lost. This information can help to improve operations and increase efficiency. Tools required for Data Analytics professionals are:
- SQL
- R Programming
- Microsoft Excel
- Power BI
- Python
- Tableau
- Hadoop
- Spark
Data analytics can do much more than bring efficiency to production. From manufacturing to content companies, every organization needs data analysts, from analyzing data to better plan workloads or using data analytics to organize content to get more views.
The Role of a Data Analyst
- Acquiring data that drive informed decision-making.
- Preparing and analyzing to understand what the data collected means.
- Explaining and communicating the meaning of the data collected to the managers who need to make effective decisions.
- Make sure the operations are stored safely for the future.
- Data Analysts need to have technological, practical, and good soft skills.
- Technological skills mean expertise in using spreadsheets, tools such as visualization, and query languages as well.
- For practical skills, a Data Analyst needs to have problem-solving skills, analytical techniques, and good visualization skills.
- Good soft skills mean the capability to work well with others and communicate successfully.
Data Analytics Process
The process involved in Data analytics has several different steps:
- Ask
Here the data analysts need to determine what the survey would look like and what makes it successful. To ascertain this they ask queries and cooperate with managers.
- Prepare
A timeline is decided during this step and the analysts identify the data needed to achieve successful results. Data can be collected from the employees. Anyone outside should not be given access to the raw data whatsoever. How to best present the data visually and what specific data is to be gathered is finalized at this step.
- Process
Surveys are sent out and it is made sure the employees gave their consent to participate. The raw data is transferred to a data warehouse for more safety.
- Analyse
Data is analyzed to find relationships and trends between them. Results should also be true to what was documented no matter what the result. Otherwise, it may reduce trust in the process and may hamper the ability to collect truthful data from employees.
- Share
The analysts should carefully share the report. The report presented to the managers should make sure that they had the complete picture. There should be proper communication within the right context so they could have productive team conversations about the next steps.
- Act
In this process, analysts work with the managers to decide the best way to make changes and take action after interpreting the data.
What are the Types of Data Analytics?
Data Analytics can be of four types:
- Descriptive Analytics
Descriptive analytics shows what occurred in the past but doesn’t advise on the future. It uses data accumulation and mining to organize past data visualizations. This can be done without using SQL or coding skills using tools like Sigma.
Descriptive analytics include:
- Annual revenue report
- Survey response summary
- Year-over-year sales report
2. Diagnostic Analytics
Diagnostic analytics is used to understand the pattern of data development. It prevents ill-informed decisions. Diagnostic analytics is used to identify issues and provides solutions.6
Diagnostic analytics include:
- Why sales went up?
- Why do products perform above expectations?
3. Predictive Analytics
This method determines future patterns and trends acquired from the data collected in the database. It predicts outcomes and the likelihood of events happening. It helps to create confident decision-makers.
Predictive analytics include:
- Businesses that use customer’s data for product recommendations
- Analyzing data to determine the likelihood of new customers responding favorably to a given campaign.
4. Prescriptive analytics
Prescriptive analytics is the most complex type that tells organizations what to do based on the predictions.
Prescriptive analytics include:
- Determining characteristics to make sure a new product is successful.
- Identifying strategies to optimize patient care in the healthcare industry to reduce risks.
What are Data Analytics Techniques?
Data analysts have numerous methods which use analytical thinking and techniques to extract information and process data from the database. The most popular methods are:
- Regression analytics
Regression analytics is used to evaluate the relationship between variables to identify trends or patterns. This is useful for forecasting future patterns of the variables.
- Factor analytics
Factor analytics is used to lower a large number of variables. Here multiple variables correspond with each other.
- Cohort analytics
Cohort analytics takes data from a given data set and breaks them into groups for analysis. These related cohorts share common attributes within a defined time.
- Cluster analytics
Here the goal is to sort data points into clusters that are internally homogenous and externally heterogeneous. Data points in a cluster are sometimes the same and sometimes different from other clusters.
- Monte Carlo simulations
This method is a strategy where every possible outcome is generated and their probability is found. It considers possible outcomes and calculates how the event happens.
- Time series analytics
Time series analytics is a technique used to identify trends and patterns over a time duration. It measures the same variable at different points over time.
- Sentiment analytics
Sentiment analytics is used to interpret the emotions carried within data which allows for discovering how the customers feel about various aspects of an organization.
What Are the Key Data Analytics Tools?
The most common programs and solutions used include spreadsheets, query languages, and visualization tools.
- Spreadsheets
It collects and organizes data. Microsoft Excel and Google Sheets are two spreadsheet applications. Spreadsheets help to identify patterns and piece the data together for each specific project. It also creates data visualizations like graphs and charts.
- Databases and Query languages
A database is a cluster of structured data in a computer system. Some Structured Query Language (SQL) is MySQL, Microsoft SQL Server, and BigQuery. Query languages help analysts to isolate specific information from a database which makes it easier to learn and understand the database better.
- Visualization tools
Data analysts use visualization tools like graphs, maps, tables, charts, etc. Popular visualization tools are Tableau and Looker. These tools convert complex numbers into interactive graphs or charts that people can understand.
Is Data Analytics for You?
Problems are always different in data analytics and the solutions need creativity which impacts others and can be life-changing. A data analyst can be part of these life-changing efforts. Learning more about this field can lead to benefits for your overall career in data analytics. Having good data analytic skills can help to build a safe and friendly environment in the organization. Data analysts require facts and clues to make decisions that provide far more effective and efficient results than gut instincts.
DATA + Business Knowledge = Results
Blending data with business knowledge will be a common process for a data analyst. The best strategy is to be more data-driven in any situation and with more practice, you will get better at finding the patterns and trends in data.
With millions of data generating every day from different mediums, it may be the best time to invest in a data analytics course that coil prepares you for the future ahead. When you use the structure of this Data Analytics Course by KPMG, we are here to guide you as you continue and evolve on your data journey.
Recommended Reads:
Importance of Using Data Analytics
Here are some importance of using Data Analytics
- Helps make better decision-making
Data analytics helps to analyze and make informed decisions by interpreting patterns, trends, and relationships between various datasets. If you ignore data and make decisions based on experience then that decision may be biased. Making better decisions helps makes the organization efficient and effective while also helping to make a profit and cut losses in the long run without any risk.
It provides effective leadership and management for the employees to work in which makes the organization better run as well as an attractive proposition for stakeholders to invest in or for employees to work for.
- Anticipate customer needs
Customer needs should be analyzed to develop longstanding relationships between the customer and the analyzing which results in the overall benefit of the analysis. Customers are increasingly using multiple channels, hence both digital and traditional data sources should be used to interact with customers. Also relevant and real-time experiences should be delivered to customers using data analytics.
- Manage risks
Efficient data and analytics will provide maximum fraud prevention and security to the analyzing. Deterrence mechanisms allow companies to detect potentially fraudulent activities and help to anticipate future attacks which prevents loss for the analysis.
Fraud risk management can be tackled by the use of proper data analytics tools which results in a safe and effective platform for organizations. Safeguarding the company’s data is a major priority that provides security to the organization as well as consumers connected to the organization through commercial, product, or services platform.
- Increase efficiency
Data analytics tools can computerize operations and tasks which frees up precious time for the staff of an organization. It can also extract patterns hidden in data to create reliable products. Optimized services and products provide better customer satisfaction which gives more profit and benefits the organization overall.
- Optimises cost
Data analytics tools such as Hadoop and Spark provide cost-effective ways for storing, processing, and analyzing large volumes of data. The development of such cost-effective ways, it could pave the way for organizations to focus more on products and services that could positively impact consumer needs and develop better consumer satisfaction.
Application of Data Analytics in Different Areas
In this modern era of Digitisation, Data analytics is huge in making businesses successful.
- Education
Our education system can be improved by using data analytics tools which could improve the overall performance of students and teachers as well. It collects analyses and uses data for further performance enhancements of teachers as well as students.
- Healthcare
Through data analytics and data visualization, the healthcare industry is improved through efficient diagnosis, medical research, and data management. It can also help in patient diagnosis, drug research, and creation, medical image analysis and managing patient data, etc.
- Logistics
Data analytics helps in generating profit, time management, the best route for delivery, and any improvements. Through optimization, it helps to analyze the market trends and customer satisfaction through speedy delivery and route optimization.
- Banking and Finance
Data analytics helps to track millions of customers through proper analysis of customer data. It helps to efficiently process and organize data properly.
- Digital Marketing and Advertising
Data analytics helps organizations reach the right customers. Using algorithms and customer data related to their search history and previous purchases data analysts identify and post ads that help to generate sales and find new customers.
Job Roles Available for Data Analytics
- Data Analyst
- Data Scientist
- Data Engineer
- Data Technician
- Business Performance Analyst
- Market Analyst
- Healthcare Analyst
- Business Intelligence Analyst
- Visualization and Reporting Analyst
Data Analytics Course by KPMG Overview
Data Analytics Course by KPMG provides extensive skills for data analyst roles to beginners as well as seasoned professionals. This professional Data analytics course is highly interactive with in-depth teaching and developed by KPMG employees with decades of experience in the industry.
Kickstart your career in Data analytics by learning core principles, gaining hands-on skills, practice using self-help videos and numerous assignments. You will get to work with data analysis tools including Microsoft Excel, Spreadsheets, R Programming, Tableau, Python, SQL, Jupyter Notebooks, Cognos Analytics, and Power BI.
Data Analytics Course by KPMG helps to gain an immersive understanding of practices used in the day-to-day job. This professional certificate serves as a launchpad for individuals by providing instructions on real-world datasets analysis, creating interactive dashboards, and presenting reports for peer review.
Data Analytics Course by KPMG provides learners with industry-leading learning having educational standards that are honed by decades of experience by KPMG global services firm, which is one of the leading services firms in the world with a pedigree that can only be acquired by hard work and experience in the field of study.
Learn key analytical skills such as data cleaning, analysis, critical thinking, data ethics, and data visualization using a highly rated Data Analytics Course by KPMG. Begin learning concrete skills that top employers all over the world are hiring for right now.
Along with specialized training and projects in Data Analytics Course by KPMG, you will also need to work to complete a case study that you can share with potential employers which could help you land the job of your dreams. The case study will have peer review which will help to develop your real-time scenario data analytics skills.
In India, there are 120,000+ in-demand job openings in data analytics with an average entry-level salary of 2.5 lakhs to 3 lakhs per annum. Data Analytics Course by KPMG provides you with job-ready skills for data analyst roles and also provides you with a much-needed foundation that will help you to launch your career toward a better future.
45% of certificate graduates after completing Data Analytics Course by KPMG have started a new career in data analytics so far and 75% of KPMG certificate graduates report career improvement.
With the demand for data analytics roles increasing worldwide and limited skilled professionals available for the role this could be the opportunity you were waiting for to change your field towards an ever-growing industry where there is no limit to growth and opportunity.
Course Details of Data Analytics Course by KPMG
- Decision-making that is data-driven and well-informed
- Process of data from dirty to clean and organized in spreadsheets
- Microsoft Excel for Data Analytics
- Data visualization using Excel and Tableau
- Data Analytics using R Programming
- Python for Data Analytics
- Database and Structured Query Language for Data Science with Python
- Data analytics and Data Visualization using Python
- Data Analytics Case study reviewed by peers
Learning Project Objectives
- Organise, clean, and interpret data with pivot tables in Microsoft Excel
- Use data indicators to create interactive dashboards
- Use SQL
- Wrangle data and create datasets
- Create dynamic Python dashboards.
- Simulate real-world data analytics scenarios critical for workplace situations.
What You Will Get to Learn Through Data Analytics Course by KPMG
- Learn how to clean and organize data using R programming and SQL.
- Use Microsoft Excel and Google spreadsheets to perform data analysis tasks.
- Create graphs and charts in Microsoft Excel and work with Cognos Analytics to make dashboards with interactive visualizations.
- Create data visualization using Python.
- Develop Python language skills and learn how to use Numpy and Pandas.
- Learn how to access data in cloud databases by using SQL and Python using Jupyter Notebooks.
Who Can Apply?
- Freshers and undergraduates
- Non-IT professionals like HR, banking, marketing, etc
- Business Intelligence professionals
- Data Analytics professionals
- Engineering professionals
6 monthly online Data Analytics Course by KPMG helps you to gain expertise in Data analytics skills with real-time projects and case studies.
- 16 courses with over 360+ hours of self-paced videos
- 300+ hours of project and exercises
- 30+ projects across 6 months of instructor-led training
- 100+ practice-based assessments
- Financial aid is available on the website
Contact:
Email Id: [email protected]
Contact: +91 6891335889
Frequently Asked Questions
Q1. How can a data analytics course help my career?
The demand for data analysts has grown exponentially over the last decade. A course in data analytics can help you become a successful data analyst across different domains. Be it data analyzing or data engineering. The increased importance of data analytics courses in India can boost your career in the industry.
Q2. What jobs can I expect from a data analytics course?
Data analytics provides skills to prevent ill-informed decision-making of managers and this course will provide you with the skills needed for an analyst role. With our data analytics course, you can secure a strong foundation in data analytics and data engineering industries.
Q3. What qualification is necessary for the course?
No specialized degree is needed for this course. But basic computer knowledge and high school level mathematics and English knowledge are necessary to complete this course.
Q4. How long will it take for me to complete all the classes?
It can take up to 9 months or you could also complete the entire course in just 3 months as it is self-paced and you can take your time working full-time or part-time on the course.
Q5. Are there any discount offers on the course?
Discount offers provided are time-sensitive. There is financial aid available on our website which you can also avail of. They also provide EMI options.
