A fundamental analytics skill that is mostly needed by most data analysts and managers.
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.
This is our second most popular course. It’s suited to any professional who needs to make decisions using business data.
Intel i3 processor, 2GB RAM
Either Mac or Windows operating system
Excel 2013 or later
Microsoft PowerPoint 2013 or later
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
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
Dummified data: what they look like and why they exist
Formatting data according to their variable types
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
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
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
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.
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.
JP has varied experience in different industries, building an analytics career with strong roots in customer service, manufacturing, retail, digital marketing, and market research. His longest and most recent engagement was with ABS-CBN, the Philippines’ biggest media network, where he led digital analytics to drive key businesses including the company’s video streaming services for both local and international markets and other owned digital properties.
Graduated from the Ateneo de Manila University with a bachelor’s degree and a masters in applied mathematics, Zac is the Gen Z analyst who is in the road to becoming a data scientist of the millennium. He was a business statistics and programming lecturer of the Ateneo, mentoring students from the John Gokongwei School of Management. In 2016, he was also a Temasek Foundation International Leadership Enrichment and Regional Networking Scholar of the National University of Singapore, having completed real analysis and mathematical statistics courses there.
Gerald has over 10 years of experience in the field of corporate education. Combining his extensive experience in corporate training and organizational development, he has been involved in developing tools and training solutions for a variety of audiences in both big and small organizations as a former Course Administrator and Developer at Avaloq, a Fintech leader in digital banking and digital wealth management in Switzerland.
A distinguished chemist, Kenon worked in the analytical laboratories of multinational corporations such as Dole and Coca-Cola. He won the 2019 Data Visualization challenge held by Data Science Philippines before committing fully to a career in Data. His aptitude for the arts and sciences, as well as his experience in technical data collection, analysis, and communication, have been key to his success as a data storyteller.
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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