Big Data Analytics
Big Data Analytics involves collecting large amounts of data from various sources and integrating this structured and unstructured data with real-time feeds and queries to uncover hidden patterns, correlations, and other valuable insights for the benefit of consumers; such as analysts and organisations.
This presents organisations with significant new opportunities and a competitive advantage derived from their most valuable asset - information. As such, Big Data helps drive efficiency and quality as well as facilitates the development of personalised products and services that further improve customer satisfaction and profit.
What you will learn?
- • The domain of Big Data
- • The drivers of advanced analytics
- • Business understanding
- • Data understanding
- • Data preparation techniques and tools
- • Modelling techniques
- • Evaluation techniques
- • Data deployment techniques
Why you should learn it?
- • Communicate effective and impactful data-driven narratives
- • Understand the role of data scientists
- • Develop analytic project lifecycles designed for particular characteristics
- • Understand the challenges behind hypothesis-driven analysis
- • Master fundamental statistical techniques in the context of the open-source analytic software environment
- • Understand the importance of exploratory data analysis
- • Understand key notions of hypothesis development and testing
- • Understand a range of advanced analytical methods; such as clustering, classification, regression analysis, time series, and text analysis
- • Interpret data into visualisations via data storytelling
- • Become active contributors to Big Data analytics projects
How will it help you?
- Organise spreadsheets and lay the foundation for easier data analysis
- Use PivotTables and Functions to effectively summarise and augment data
- Data profiling techniques that save time, energy, and resources
- Assess data distributions and statistical relationships
- Simple statistical techniques to examine distributions of different subgroups
- Examine linear relationships through the Pearson Correlation Coefficient via a combination of scatterplots and Excel formulae
- Unlock analytics capabilities through expert-level visualisation techniques
- Learn Power BI essentials to create descriptive analytic charts
- Basic & strategic charting that help decision-makers digest large quantities of data faster
- Create spark lines, boxplots, and line graphs for analysis towards decision-making
- Advanced chart tools to develop a higher level of actionable insight
- Visualise data as well as design dashboards for different audiences and purposes, exploration, reporting etc
- Dashboarding that enables an entire team to work with the data and find creative insights
Who is it for?
- Data analysts looking to add this skill to their portfolio
- Database professionals and managers of business intelligence
- Big Data groups looking to enrich their analytic skills
- College graduates investigating data science as a career field
Live training and coaching
Role play & video presentation
Interactive 2-way communication
Certificate of Attendance
8 hours / day
Total: 24 hours
Online / Virtual Training
via Microsoft Teams, Zoom, or Cisco
Note: Minimum 10 participants. Maximum 20 participants.
The Voices of Our Valued Clients
Duopharma Malaysia Sdn Bhd
Malaysian Automotive Lighting Sdn. Bhd.
Boustead Heavy Industries Corporation Berhad
Employees’ Provident Fund (KWSP), Malaysia
Construction Development Corporation Ltd, Bhutan
Bank Rakyat, Malaysia
Affin Bank Berhad, Malaysia
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