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Instructor-led training
Big Data Analytics Training in London and Live Online

Big Data Analytics

Develop practical analytics workflows for larger datasets. Prepare data, query and process it with suitable distributed tools, and validate results before communicating findings.

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Price:
Price on request

Contact us for current fees, dates and exam arrangements.

Intermediate

Have basic SQL and Python knowledge or equivalent data-analysis experience.

5 days to complete
Available online
& in class

Select your preferred method

Course overview
Course dates
  • In Classroom
  • Live Virtual
  • 1 - 1 Training
  • Corporate Training
  • Onsite Training
Introduction
Develop practical analytics workflows for larger datasets. Prepare data, query and process it with suitable distributed tools, and validate results before communicating findings.


This instructor-led course combines clear explanations with guided exercises and practical scenarios. Work through examples relevant to the subject, review alternative approaches and practise checking your results rather than relying on a demonstration alone.
You will develop a structured approach to implementation, troubleshooting and documentation. The trainer can adapt examples to the agreed learning needs and available training environment. Confirm the course duration, software or lab requirements, delivery arrangements and fees with London IT Training before booking.
This is professional development training. It does not automatically award a third-party vendor certification.
What the course covers
Flexible Ways to Learn

Study your way with flexible learning options designed to fit around your schedule.

Small Groups

With small groups of students, our instructors can work closely with each student

Flexible Class Schedules

Our class schedules are flexible on weekdays, weekend or evening to suit your schedule.

Experienced Instructors

Our instructors follow a modified and personalised approach to engage students during class

Hi-Tech lab Facilities

Lab arrangements vary by course. Confirm access and equipment requirements before booking.

Prerequisites
What you’ll gain

Apply analytical problem framing in a practical course exercise.

Apply data preparation in a practical course exercise.

Apply distributed data processing in a practical course exercise.

Apply sql and analytical calculations in a practical course exercise.

Develop skills for your next step
Relevant career pathways
Technical Practitioner:

Apply the course skills to relevant technical tasks.

Technical Consultant:

Assess requirements and recommend practical implementation choices.

Syllabus

Course context and practical foundations
Review the course objectives and relevant concepts. Set up a suitable training environment, identify a realistic example and agree how to validate the results.

Define the question, data requirements, assumptions and measures of success. Establish a baseline before choosing tools.

Inspect schemas, missing values and data quality. Apply repeatable transformations and retain traceability to source inputs.

Explore Spark DataFrames, transformations and execution concepts. Consider partitioning and unnecessary data movement.

Use joins, grouping and window-style analysis where appropriate. Validate totals and compare results against smaller reference datasets.

Understand incremental processing, event time, checkpoints and operational dependencies at an appropriate level.

Investigate bottlenecks, document limitations and present findings with clear evidence and suitable visualisations.

Complete an integrated exercise using sample data or an isolated training environment. Test the result, document decisions and troubleshooting steps, and identify improvements and next learning objectives.

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FAQs

Who is this course for?
Develop practical analytics workflows for larger datasets. Prepare data, query and process it with suitable distributed tools, and validate results before communicating findings.

Have basic SQL and Python knowledge or equivalent data-analysis experience. Understand tables, aggregations and data-quality checks. Confirm access to a suitable Spark or distributed analytics training environment.

Analytical problem framing; Data preparation; Distributed data processing; SQL and analytical calculations; Streaming and pipeline concepts; Performance and communication.

No. This is professional development training. It does not automatically award a third-party vendor certification.

Contact London IT Training to discuss classroom, live online and corporate delivery arrangements.

Contact the training team for current duration, available dates, fees and software or lab requirements. Do not assume that licences, materials or examination fees are included.

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Talk to one of our advisers about dates, delivery options and certification routes. We’ll call you back within 1 working day.

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