SheLovesData Sydney: Introductory Data Analytics Workshop (Feb 2019)
By: Shara Jamei
Tags: Data Visualization, Elt, Data, Data Analysis, Charts

The focus of the even was about data, data analytics, data-related terms, sql and data visualization.

Talking about data and data analytics:

What does it mean to be a data analyst?

Data analysis is the art of mixing mathematics, machine learning and business experience to support decision making in the company based on information you can extract and combine from given data. To be a successful data analyst you should be able to define the main questions to answer, then gather data, analyze it and interpret the result and finally, the main skill of a data analyst is to be able to tell stories and convinced management team or stakeholders to make decision based on their stories. Finding the right question to answer is one of the tricky parts of this role. Based on size of the company or project, people may participate on different aspect of data analytics based on their focus on gathering data, cleaning it, visualize it or telling stories. Scientists find that data analysts would get good result if they put 20% of their time on making reports — ELT (Extract, load and transform) and reports — and 80% to find the solution and storytelling, but in real world, more than 80% of focus is on making reports rather than finding solutions.

What is ELT?

ELT is the process of transforming raw data to meaningful information. Steps are:

Extraction: Extract data from various resources and data formats like

· Relational DB (SQL)

· NoSQL DB: For unstructured data like document-oriented, column-oriented, graph-based or organized as a Key-Value store

· Flat file

· XML (document-oriented)

Data in this step is corrupted, incomplete and not clean.

Load: Load to data warehouse

Transform: Applying sets of rules and functions to raw data to make it standard, some main steps could be:

· Filtering: Filter none-related attributes

· Cleaning: filling up the NULL values with some default values, mapping abbreviations

· Joining/ Splitting: joining multiple attributes into one or extracting one attribute from multi attributes

· Sorting

Introduction to SQL

Practicing basic SQL commands on real life data, introduce select, concat, order, limit and group. To me, this part was more about improving my teaching and communication skills as I was helping others to be able to play with the SQL.

Hands-on SQL

Data Visualization:

Visualization is one of the most important part of data analytics as you are making the result easy to read and understandable for those who are busy and don’t have time to spend on every detail or they may not be interested in data, but they need information. A good data visualization should tell visual story, answer specific questions, be tailored for the target audience, transfer your insights and findings quickly and it shouldn’t need IT knowledge to be understandable.

The most common way of visualizing data is by creating graphs and charts. A good chart should be simple but informative. They are different type of charts like pie, bar and line charts, you should be mindful of choosing the best one for your data. There are some tips to create good charts.

Tips to create better charts

· Make sure you are choosing the right chart

· Don’t add unimportant information to the chart

· Make sure main information is in the chart and easy to understand

· Don’t overload your chart with information

· Use axis, sometimes you can drop one axis (and grid-lines) and add compared values to the chart

· Don’t use 3Ds unless it really adds extra information

· Don’t use pie charts to compare more than 5–6 values and the sum of values should be 100

· If they time sequence is not important, order values either ascending or descending

· If the category names are too long, vertical chart would be a better choice

· Don’t use more than 6 color in a chart

· Don’t use similar colors in compared columns

· Don’t use too much animations

Should be aware that data visualization is not only about making charts, it is using charts to telling a better visual story.

Yellowfin Dashboard

Hands-on visualization session

After learning some about visualization and tips of making charts, we practiced on real world visualization using yellowfin. Making reports on data given about “The Titanic” to answer some imaginary business questions, try to think of new questions about this matter and transform reports to charts and making dashboard and try to write an attractive visual story were some of hands-on activities which helped to understand the theories in practice.

What else?

Other than all these technical information and practices, I found the stretching part between sessions quite helpful. It didn’t take more than 2–3 minutes, but it gave energy to be focused and continue learning. I think it can increase team work if we do some group stretching for 2–3 minutes every day all around the office at same time.