Course description
Data analytics uses complex algorithms and computer software to process large amounts of raw data to understand patterns, trends, and relationships within that information. Nowadays, data analytics is most often used inside businesses’ managerial and promotional contexts. It may help you see patterns, anticipate actions, and zero in on the most productive strategies. Data analytics is widely used in the modern world, from the most basic uses of web analytics to the complex analytics used by businesses to make decisions, predict outcomes, and improve operations. Data analytics can be performed on a small scale, such as analyzing the number of customers who visited a website, or on a large scale, such as analyzing the text and audio of a video to detect speech patterns.
How has data analytics transformed the functioning of organizations today?
Data analytics efforts are transforming how businesses operate and interact with customers. Analytics enables you to identify patterns and trends in your data that were previously hidden or unnoticed, detect changes that impact customers, assess the value of marketing campaigns, streamline operations and much more. Through data analytics, organizations can gain a competitive edge over their rivals. The ultimate goal of data analytics is performance enhancement.
Upcoming start dates
Suitability - Who should attend?
Who should attend?
Rcademy’s training course is ideal for data-oriented individuals as well as enthusiasts such as:
- Data Managers
- Business Analysts
- Managers and professionals from different walks of life
- Financial analysts/financial statement analysts
- Quantitative analysts
- Business architects
- Project manager
- IT professionals
- Graduates and Scholars
- Entrepreneurs
Outcome / Qualification etc.
Rcademy’s Data Analytics Certification Training Course is aimed at the following objectives:
- To gain an understanding of fundamental concepts of data analytics and its applicability in various areas of business
- To gain an understanding of different types of analytics: descriptive, prescriptive and predictive analytics as well as their linkage with each other
- To discover and extract valuable insights from data that is otherwise ignored
- To explore deeper aspects of data and find hidden patterns and trends
- To learn to use data analytics techniques for the solution of real business problems
- To learn the practical use of principles of data analytics in business
- To enhance business decision-making through efficient data analytics=
- To Utilise data analytics techniques in improving business activities such as better forecasting, detection of fraud, etc.
- To learn effective ways of data presentation through various tools of data visualization to communicate your findings to various stakeholders
- To learn about emerging trends and practices of Data Analytics
Training Course Content
Module 1: Introduction to Data Analytics
- Data Science vs Data Analytics
- Use of Data Analytics in Business
- Types of Analytics
- Data ecosystem and Lifecycle
- Use cases of Data Analytics
- Types of evaluation
Module 2: Descriptive Analytics
- Descriptive statistics
- Data aggregation and data mining
- Examples of descriptive analytics
- Common Methods and Techniques of descriptive analytics
Module 3: Diagnostic Analytics
- Root cause analysis
- Data discovery
- Drill-down
- Examples of diagnostic analytics
- Correlation
Module 4: Predictive Analytics
- Application of predictive models
- Decision trees
- Neural networks
- Text analytics
Module 5: Prescriptive Analytics
- Predictive vs Prescriptive
- Prescriptive decision models
Module 6: Data Analytical Skills
- Critical thinking
- Hypothesis formulation and testing
- Data wrangling
- Data visualization
- Machine learning
Module 7: Steps in Data Analytics
- Goal setting
- Priority setting
- Data Generation and Data Gathering
- Data cleansing
- Data analysis
- Data interpretation
Module 8: Data Mining
- Data Classification
- Regression analysis
- Anomaly detection
- Clustering analysis
Module 9: Data Visualisation
- Charts and plots
- Multivariate data visualization
- Visualization techniques: pixel, geometric, icon-based, hierarchical visualization
- Visualization tools
Module 10: Exploratory Data Analysis
- Use of Exploratory Data Analysis
- Box plot
- Pareto chart
- Handling missing values and handling outliers
Module 11: Business Intelligence
- Application of Business Intelligence in corporate
- Business intelligence technologies
- Online Analytical Processing
- Dashboards
Module 12: Deep Learning
- Principal Component analysis
- Time series analysis
- Neural Networks
- Machine learning basics
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Rcademy
Rcademy is a global training and consultation organisation set out to bridge the gap between you now and what you can be in the near future. We are facilitators of knowledge impartation. Our team of established and experienced training enthusiasts...