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Data Analytics Fundamentals

Course Overview

In this practical training, we teach you the key fundamental  skills relating to data analytics concepts, statistical analysis, data preparation, data summarisation and data visualization.

This will help you to better understand your data and make the most of it for your business.

Course Objectives

By the end of this Data Analytics Training, you will be able to:

  • Understand the key concepts relating to the application of data analytics in business.
  • Understand and apply key statistical analysis concepts.
  • Import data into a spreadsheet and prepare it for analysis using data cleansing and filtering techniques.
  • Summarize data using pivot tables and pivot charts.
  • Understand and apply data visualization techniques and tools.
  • Create and share reports and dashboards in a data visualization tool.

Course Outline for Data Analytics

Section 1: Key Data Analysis Concepts and Statistical Analysis

Key Concepts

  1. Identify the main types of data analytics: descriptive, diagnostic, predictive, prescriptive, quantitative, qualitative.

  2. Outline the business benefits of data analytics: identifies patterns/trends, improves efficiency, supports decision making, presents information effectively.

  3. Identify the main phases of data analysis: business understanding, data understanding, data preparation, modelling, evaluation, deployment.

  4. Recognize data protection considerations when analyzing data like: anonymize personal data if possible, comply with applicable data protection regulations.

Statistical Analysis

  1. Describe measures of central tendency of a data set: mean, median, mode.

  2. Calculate the central tendency value of a data set using a function: mean, median, mode.

  3. Describe measures of variation of a data set: quartiles, variance, range.

  4. Calculate the variation of a data set: quartile, variance, range.

Section 2: Data Preparation

Importing Data, Shaping it & Filtering what you want

  1. Import data into a spreadsheet application: .csv file, spreadsheet, website table, database table.

  2. Remove duplicate data.

  3. Validate that given values belong to a reference data set using the vlookup function.

  4. Validate that given values belong to a specified range using one or more if functions.

  5. Extract values from a string using text functions: left, right, len, mid, find.

  6. Format a data set as a built-in table.

  7. Insert and use table slicers.

Data Summarization

Aggregation With Pivot Tables

  1. Change the method of aggregation for a value: sum, average, count, minimum, maximum.
  2. Display multiple aggregation values.
  3. Display values as: % calculation, difference from specific values, running total, ranked.

Frequency Analysis With Pivots

  1. Automatically, manually group data and rename groups.
  2. Ungroup data.

Filtering Pivots

  1. Use the report filter.
  2. Insert and use slicers to filter single, multiple pivot tables.
  3. Insert and filter a timeline.

Using Pivot Charts

  1. Insert a pivot chart for an existing pivot table.
  2. Create a pivot chart from fields in a data set.

Data Visualization

Concepts and Setup

  1. Understand the concept of data visualization using reports and dashboards. Outline common visualizations like: charts, key performance indicators (KPIs), maps.

  2. Recognise common data visualization tools and their functions like: visualise data, publish and share business intelligence.

  3. Understand good design practice in reports and dashboards like: clean and uncluttered layout, descriptive titles, consistent fonts and colour, use of colour for emphasis and understanding.

  4. Import a data set from a spreadsheet into a data visualization tool and save the file.

Visualization

  1. Create tables in a report.

  2. Visualise data as a chart: column, bar, line, pie.

  3. Apply, edit font and background conditional formatting to show: high/low values, above/below average values.

  4. Apply, edit data bars.

  5. Apply, edit visual level filters.

Publishing and Sharing

  1. Publish a report.
  2. Create a dashboard.
  3. Share a report, dashboard using a link. Share a report to web.

Register for Data Analytics Training

How to Register: Simply fill this Online Registration Form. The Intellisoft Training Officer will get in touch with you to confirm your seat shortly. You can call at at +65 6296-4663 if you have any questions.

Do You Have Any Questions

on Course Fee, WSQ Grant or Funding?

Ask Us. We’ll be happy to assist you.

Course Duration for Data Analytics Fundamentals Training : 2 Full Days

Training Schedule
23, 24 Jun 2022 (Classroom)
21, 22 Jul 2022 (Classroom)
22, 23 Aug 2022 (Classroom)
19, 20 Sep 2022 (Classroom)

Call (65) 6296-4663 for Details.