BCS - Level 4 Certificate in Data Analysis Tools

Duration

Duration:

Just 4 Days

Method

Method:

Classroom / Online / Hybrid

Next date

Next date:

7/2/2022 (Monday)

Overview

On this 2-day accelerated BCS Level 4 Diploma designed for Apprentices, you’ll learn key skills needed to master Data Analysis Tools.

You’ll be immersed in the curriculum through our unique Lecture | Lab | Review technique, which allows you learn and retain information faster than traditional courses.

On this course you'll cover the range of concepts, approaches, tools and techniques that are applicable to Data Analysts. You will learn skills and knowledge applicable to Data Analysis Tools and the underlying principles and processes of data integration.

Key areas covered include learning to:

  • Describe the purpose and outputs of data integration activities
  • Explain how data from multiple sources can be integrated to provide unified data
  • Discover programming languages and how they are used to integrate data and prepare it for analysis
  • Explain the nature and challenges of data volumes and types being processed through integration activities
  • Develop testing strategies to test unified data for a range of states
  • Demonstrate an understanding of the capabilities of statistical programming languages and proprietary tools
  • Prepare data for analysis using a series of techniques
  • Carry out data analysis

During the course you’ll sit BCS Level 4 Certificate in Data Analysis Tools Exam. Don’t pass the first time? Don’t worry – you’ll be covered by our Certification Guarantee .

Four reasons why you should sit your BCS Data Analysis Tools course with Firebrand Training

  1. You'll be BCS Data Analysis Tools trained and certified faster. Learn more on this 4-day accelerated course. You'll get at least 12 hours a day of quality learning time in a distraction-free environment
  2. Your BCS Data Analysis Tools course is all-inclusive. One simple price covers all course materials, exams, accommodation and meals – so you can focus on learning
  3. Pass BCS Data Analysis Tools first time or train again for free. Your expert instructor will deliver our unique accelerated learning methods, allowing you to learn faster and be in the best possible position to pass first time. In the unlikely event that you don't, it's covered by your Certification Guarantee
  4. Study BCS Data Analysis Tools with an award-winning training provider. We've won the Learning and Performance Institute's "Training Company of the Year" three times. Firebrand is your fastest way to learn, with 108.073 students saving more than one million hours since 2001

Benefits

Curriculum

1. Processes and Tools Used for Data Integration

In this topic, the apprentice will describe how data integration is achieved through the manipulation of data from different sources. They will also learn about how this data is manipulated using programming languages and how it is prepared for analysis. You'll be able to :

1.1. Describe the purpose and outputs of data integration activities.

  • Business need for analysis
  • Non-functional requirements (such as speed and time available)
  • Information structure and rules relevant to the business
  • Rationale for using and integrating data from multiple sources
  • Importance of data in a business context

1.2. Explain how data from multiple sources can be integrated to provide a unified view of

the data.

  • Reasons for using data from multiple sources
  • Importance of data source quality to improve the quality of results
  • Filtering data to ensure only relevant data is combined to underpin business
  • objectives
  • Ensure data is selected in line with current legislation
  • Data integration techniques
    • Common user interface
    • Virtual integration
    • Physical data integration (for example ETL (Extract - Transform - Load))

1.3. Discover how programming languages for statistical computing can be applied to data

integration activities to filter and prepare data for analysis.

  • Programming constructs
    • Sequence, selection and iteration
    • Modularisation, coupling and cohesion
  • Commands for manipulating data (for example, but not limited to)
    • Select and Select* statements
    • From
    • Where (such as but not limited to; AND, OR, use of Wildcards and ordering)
    • Joins (inner and outer, right, left, Full, Union and Select into)
    • Joins with duplicate values
    • Joining on multiple fields
  • Single queries
  • Multiple queries
  • Expressions
  • Functions (such as but not limited to; Avg(), Count(), Max(), Min(), Group by,
  • Round(), Cast(), Convert(), ISNULL ())
  • Querying multiple tables in different information
  • Selecting the first/last of occurrences
  • Implicit data conversion

1.4. Explain the nature and challenges of data volumes and types being processed through

data integration activities.

  • Big data sets
  • Qualitative data versus quantitative data
  • Technical requirements for managing large data set (such as, but not limited to; the
  • location of data and challenge of restrictions due to the computer architecture)
  • Data warehousing
  • Data migration
  • Master data management
  • Integration design
    • Business requirements for integration
    • Objectives and deliverable
    • Business rules
    • Support models and SLAs
  • Non-functional requirements
  • Data integration tools (such as future scalability, implementation and support costs)
  • Data synchronisation (such as data ownership, frequency of updates, format,
  • security, data quality, performance and maintenance)

1.5. Develop appropriate testing strategies to ensure that unified data sets are correct,

complete and up to date.

  • Check against business requirements
  • Test for a variety of states (such as, but not limited to; presence, completeness,
  • configuration and format, that data is valued and that data is not fragmented)
  • Business testing & technical testing
    • Technical acceptance testing (TAT)
    • User acceptance testing (UAT)
    • Performance stress tests (PST)

2. Industry Standard Tools and Methods for Data Analysis

In this topic, the apprentice will describe and use a range of tools, techniques and methods to prepare and analyse data. The successful apprentice should be able to:

2.1. Demonstrate the data manipulating, processing, cleaning and analysis capabilities of statistical programming languages and proprietary software tools capabilities and functions of statistical programming languages (such as, but not limited to; R, Python, SPSS, SAS, SQL, Microsoft Excel and VBA, Julia, Hadoop and Hive, Scala)

2.2. Demonstrate how to apply statistical programming languages in preparing data for analysis and conducting analysis projects.

  • Preparation techniques (such as, but not limited to; searching and sorting, grouping,
  • filtering, macros and modelling)
  • Data cleaning to remove a range of data issues (such as, but not limited to; errors,
  • invalid values, data that is out of range, outliers)
  • Processing and analysing:
    • Mean, Median, Mode and Range
    • Probability
    • Bias
    • Statistical significance
    • Linear Regression (simple & multiple)
    • Logistics Regression (simple & multiple)
    • Scatter plots and correlation
    • And/Or probability
    • Stem and leaf plots
    • Factorials
    • Box and whisker plots
  • Methods for presenting results (such as, but not limited to; tables, charts and
  • graphs, correctly arranged and presented using suitable language)
  • Presenting for data analysts
  • Working with people

Exam Track

The format for the exam is a one-hour, closed book multiple-choice exam consisting of 40 questions. The pass mark is 26/40 (65%).

If you're taking the exam in a language that is not your native/official language, you are entitled to 25% extra time and are allowed to use your own paper language dictionary to translate during the exam.

What's Included

Exam and Firebrand developed course materials

Your accelerated course includes:

  • Accommodation *
  • Meals, unlimited snacks, beverages, tea and coffee *
  • On-site exams **
  • Exam vouchers **
  • Practice tests **
  • Certification Guarantee ***
  • Courseware
  • Up-to 12 hours of instructor-led training each day
  • 24-hour lab access
  • Digital courseware **
  • * For residential training only. Doesn't apply for online courses
  • ** Some exceptions apply. Please refer to the Exam Track or speak with our experts
  • *** Pass first time or train again free (just pay for accommodation, exams and incidental costs)

Prerequisites

There are currently no prerequiustes for this course

Are you ready to get certified in record time?

We interview all applicants for the course on their technical background, degrees and certifications held, and general suitability. If you get through this screening process, it means you stand a great chance of passing.

Firebrand Training is an immersive training environment. You must be committed to the course. The above prerequisites are guidelines, but many students with less experience have other background or traits that have enabled their success in accelerated training through Firebrand Training.

If you have any doubts as to whether you meet the pre-requisites please call (0)8 52 50 01 66 and speak to one of our enrolment consultants, who can help you with a training plan.

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