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Data Analytics Certification Training Course » BDM12

Data Analytics Certification Training Course

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17 Mar - 21 Mar, 2025Live Online5 Days£2850Register →
05 May - 09 May, 2025Live Online5 Days£2850Register →
21 Jul - 01 Aug, 2025Live Online10 Days£5825Register →
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17 Dec - 19 Dec, 2025Live Online3 Days£1975Register →
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17 Feb - 19 Feb, 2025Barcelona3 Days£3825Register →
03 Mar - 14 Mar, 2025Seoul10 Days£8025Register →
21 Apr - 02 May, 2025Nairobi10 Days£8350Register →
12 May - 16 May, 2025London5 Days£4750Register →
18 Jun - 20 Jun, 2025Barcelona3 Days£3825Register →
28 Jul - 01 Aug, 2025Toronto5 Days£5150Register →
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15 Oct - 17 Oct, 2025Kuala Lumpur3 Days£3375Register →
03 Nov - 07 Nov, 2025London5 Days£4750Register →
03 Dec - 05 Dec, 2025Athens3 Days£3825Register →

Why select this training course?

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.

What industries are using data analytics?

When it comes to the insights derived from data, most industries are looking for more than just numbers. Data analytics is increasingly becoming a key component in business decision-making, enabling smarter and faster decisions and improved productivity. From retail, banking, travel and hospitality to agriculture and the public sector, energy efficiently makes the best of data analytics. The application of data analytics in these industries has led to a huge increase in the efficiency with which they operate, with reductions in cost being one of the main benefits.

Rcademy’s Data Analytics Certification Training Course is intended for anyone who wants to learn about data analytics. You will get an overview of the major analytical processes and learn how to work with data in various ways. The course will include the following topics: Introduction to Data Analytics, Data Mining and Data Management, Statistical Analysis, Visualization and Presentation. This course is a complete guide to learning industry-standard data analytics practice. It starts with understanding the data analysis pipeline and then discusses data management, statistical analysis and visualization. This certificate course will give you the skills to implement your data analytics initiatives. You’ll understand how to collect, analyze and apply data in a way that supports business growth.

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

What are the course objectives?

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

How will this course be presented?

  • Interactive sessions
  • Use of case studies
  • Management games
  • Learning preparation of reports, charts, graphs
  • Real-time exercises
  • Problem-solving and Group discussion sessions

What are the topics covered in this course?

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

Participant Reviews

LA
Leena Alsulaiman
The course was incredibly informative and helpful. Thank you to everyone who supported and guided us throughout the journey!
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