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Excel Analytics Ninja

A fundamental analytics skill that is mostly needed by most data analysts and managers.

Public Training

    Private Training

    For 20+ students,
    we offer private/custom
    training solutions

    Course Overview

    Well told data stories are change drivers within the modern organization.
    Influence decision makers by designing data stories that are engaging and clearly communicate insights and actions.

    Some executives mistakenly believe that the majority of value in business datasets is only unlocked by applying advanced statistical and machine learning techniques. In practice, most of the value in business data is derived by asking relatively simple questions that can be answered using basic data manipulation and common metrics (e.g. averages, totals, counts and percentages).

    That said, the ability to ask the right business questions and answer them with the right metrics is a fundamental analytics skill that is sorely lacking in the skillset of most data analysts and managers. Why? University statistics and math programs don’t prepare graduates for the challenges and pace of the business setting. In this Excel based course, participants will learn how to progress through the full data driven decision making process, from identifying the business question through to hypothesis development, data manipulation and presenting of results.

    Who is this course suitable for?

    This is our second most popular course. It’s suited to any professional who needs to make decisions using business data.

    Prerequisites

    None

    Required Laptop Specs

    Intel i3 processor, 2GB RAM
    Either Mac or Windows operating system

    Software Requirements

    Excel 2013 or later
    Microsoft PowerPoint 2013 or later

    Course outline

    Day 1
    I. What is the end goal of this course?
    9:00am - 9:05am

    II. Keys to Effective Analytics: Exploratory Data Analysis (EDA)
    9:05am - 9:15am

    What is EDA?

    Context: understanding the data and its source

    Variables: knowing and classifying data into various data types

    Wrangling: performing basic data munging to address missing values, outliers, input errors

    Analysis: discovering univariate and bivariate relationships in the data

    III. Context and Variables: Understanding the Data
    9:15am - 9:45am

    Questions to ask of your dataset

    What are the different types of data?

    Fancy statistics terms vs. their common business meanings

    Classifying the variables of the course dataset

    Numeric variables: continuous and discrete

    Categorical variables

    Dummified data: what they look like and why they exist

    Formatting data according to their variable types

    IV. Wrangling: Using Formulae, Filtering, and Sorting to Manipulate Data
    9:45am - 10:15am

    Querying your data

    Sorting data according to various dimensions and multiple levels

    Identifying and extracting metrics needed to generate or prove certain insights

    Manipulating text or string data

    Working with dates

    Wrangling data through arrays

    Optional wrangling:

    V. Q&A / Break
    10:15am - 10:30am
    VI. Univariate Analysis and Multivirate: Leveraging Excel Features for Analyzing Data
    10:30am - 12:00nn

    Querying your data to make relevant analysis

    Choosing the right metrics, according to the insight to be supported

    Calculating percentages and understanding their meanings

    Summarizing your data into logical groupings

    Other ways to summarize your data

    VII. Lunch
    12:00nn - 1:00pm
    VIII. Workshop
    1:00pm - 4:00pm
    IX. Group Work Submission Deadline
    4:00pm - 4:15pm
    X. Group Presentations, Feedback and Wrap
    4:15pm – 5:00pm
    Day 2
    I. Day 1 Recap
    9:00am - 10:15am
    II. Q&A / Break
    10:15am - 10:30am
    III. Using Elegant Data Visualization for Reporting
    10:30am - 12:00nn

    When to use and how to create non-standard data visualizations

    Reference lines to support your insight

    Funnel Charts to show sequential steps and subsets

    Tornado / Divergent Bar / Bi-Directional Bar Charts to show comparisons

    Funnel Charts to show sequential steps and subsets

    Optional charts for advanced audiences

    IV. Lunch
    12:00nn - 1:00pm
    V. Workshop
    1:00pm - 4:00pm
    VI. Group Work Submission Deadline
    4:00pm - 4:15pm
    VII. Group Presentations, Feedback and Wrap
    4:15pm - 5:00pm

    Learn from one of our Lead Trainers

    Martin Ng Lead Data Storytelling Trainer

    With more than a decade of teaching and training experience, Martin has trained both corporates and students in the field of business IT, data analytics and data storytelling. He specializes in offering practical steps to guide data projects by applying the Design Thinking methodology to data analytics.

    Jay Manahan Lead Data Storytelling Trainer

    A data storytelling expert, Jay is concurrently a trainer at DataSeer and Head of Operations at Magpie.IM, an online payments startup. Jay holds an MBA and B.S. in Mathematics from Ateneo de Manila University. He was a winner of the 2017 Grab Data Visualization challenge.

    Pricing

    Course
    Date
    Location
    Price
    To be announced

    For 20+ students, Contact us for private/custom training solutions.

    Prices are VAT exclusive. / Training fee is inclusive of lunch, coffee and snacks.

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