BCS - Level 4 Certificate in Data Analysis Tools

Dauer

Dauer:

Nur 4 Tage

Methode

Methode:

Klassenraum / Online / Hybrid

nächster Termin

nächster Termin:

27.9.2021 (Montag)

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 .

Benefits

In einem Firebrand Intensiv-Training profitieren Sie von folgenden Vorteilen:

  • Zwei Optionen - Präsenz- oder Onlinetraining
  • Ablenkungsfreie Lernumgebung
  • Eigene Trainings- und Prüfungszentren (Pearson VUE Select Partner)
  • Effektives Training mit praktischen Übungseinheiten und intensiver Betreuung durch unsere Trainer
  • Umfassendes Leistungspaket mit allem, was Sie benötigen, um Ihre Zertifizierung zu erhalten, inklusive unserer Firebrand Leistungsgarantie.

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

Prerequisites

There are currently no prerequiustes for this course

Sind Sie sich unsicher, ob Sie die Voraussetzungen erfüllen? Wir besprechen gerne mit Ihnen Ihren technischen Hintergrund, Erfahrung und Qualifikation, um herauszufinden, ob dieser Intensivkurs der richtige für Sie ist.

Erfahrungsberichte

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"BCSIDBA is an intensive, but rewarding course and is highly executed very well through the use of Firebrand."
Iman Hussain, Pareto Law. (24.5.2021 (Montag) bis 29.5.2021 (Samstag))

"The instructor was excellent at teaching, very knowledgeable and patient with a newbie like myself! I really enjoyed the course and would recommend it!"
S.M., The WOS Group. (19.10.2020 (Montag) bis 24.10.2020 (Samstag))

"I had planned on attending the CISMP at the Firebrand training facility but due to the current restrictions the course was changed to online. I was apprehensive on how this would pan out and pleased to say I was pleasantly surprised. The course was very well structured and the instructor very knowledgeable and engaging. The only downside is that I have to wait to sit the exam but feel confident that I will be successful. Well done Firebrand in such challenging times!"
N.W.. (30.3.2020 (Montag) bis 2.4.2020 (Donnerstag))

"I found the CISMP course excellent as it gave me all of the relevant information and understanding condensed in a week. The trainer was a subject matter expert and excellent keeping the subject matter interesting and enjoyable. I would be happy to recommend this training."
Philip Gilmore, Northern Ireland Civil Service. (6.1.2020 (Montag) bis 9.1.2020 (Donnerstag))

"I like this concept of being away of work and home, it does help a lot. The instructor is great , I like the way he drived the training sessions."
Jorge Neves. (28.10.2019 (Montag) bis 31.10.2019 (Donnerstag))

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