Reporting and Prediction of Big Data

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Course number 900-059-EQ
Platform Tableau Public & Google Cloud Platform
Duration 45 hours
Prerequisites Basic understanding of databases is preferred. Otherwise, Excel spreadsheet processing experience will suffice and a basic understanding of computer systems.
Target Audience Data analysts; Computer Analysts; Individuals in any role dealing with small or large amounts of data needing to analyze it and produce insightful reports.
Dates September 6 – November 6 ( no class on September 27-27 and October 9)
Instructor Diego Perea
Room BH-311
Schedule Monday & Wednesday  6: 30 p.m. – 9:30 p.m.
Emploi-Québec fee $90.00
General public fee $724.34

 

Course Description
Please note that this is a non-credit course.
This course provides an introduction to data mining and reporting. It gives the participants the concepts and software skills needed to research, load, process and analyze data to obtain the insights that big data provides. It pays special attention to developing the software skills in Tableau and Google Big Query to process the data and prepare presentations and dashboards that highlight the data insights and the prediction and forecast capabilities.

The course methodology is based on lectures led the instructor who will present the concepts using industry examples. Each lecture is followed by a lab using real data. In the labs, the participant will complete specific tasks to reinforce the concepts seen in the lecture.

NB: Certificate provided for all participants who have completed 80% of course hours

 

Topics Covered in this Course
1.     Data processing stages in Data mining
2.     Hardware and software systems for data mining
3.     Extracting, Transforming and Loading data
4.     Principles of Data analysis
5.     Preparing reports and dashboards displaying the data insights
6.     Forecasting and Prediction
7.     Connecting to Big data systems

 

Weekly Topics
Please note that the instructor reserves the right to modify this schedule
Week 1 Introduction and software and data preparation lab
Week 2 Topics 1 and 2
Data processing stages in Data mining
Hardware and software systems for data mining
Week 3 Topic 3
Extracting, Transforming and Loading data
Week 4 Topic 4
Principles of Data analysis
Week 5 Topic 5
Preparing reports and dashboards displaying the data insights
Week 6 Topic 6
Forecasting and Prediction
Week 7 Topic 7
Connecting to Big data systems
Week 8 Projects presentation and closing lecture.

 

SOFTWARE TO BE USED

For the course, we will mainly use Tableau public to load, process, analyze data and produce reports and dashboards. Other complimentary software we will use are: MS Excel, MS Access and text editors like Notepad. Other data analytics software tools will be addressed in the course to give the participant a holistic view of data mining rather than a Tableau-centered one. Each participant will bring his/her own laptop where the software will be installed and will use it to process the data. We will use Tableau Public platform to publish and share the reports and dashboards. 

DATASETS

During the course, we will use the following datasets in several labs to re-inforce the concepts. In these labs, we will perform the different stages in the data mining process. Namely, ETL (Extraction Transformation and Load), Analysis and Reporting.

  1. Uber trip data: trip information including Uber service type, source, destination, distance, duration and paid fare. Example https://public.tableau.com/shared/MKW3XJFM3
  1. Mobile video trending data: Characterization and trending analysis of video consumption from mobile devices. Example https://public.tableau.com/views/Lab3A/DashboardDeviceTypeGrowth
  1. Google Cloud NOAA data: Worldwide meteorological information including temperature, wind and rain for more than 60 years. Example https://public.tableau.com/shared/ZXMBBQHW3
  1. Google Cloud Shakespeare data: word count of all Shakespeare works. Example https://public.tableau.com/views/Shakespearedataset1/Sel_wordsSoup

In addition to these datasets, participants are welcome to bring their own data to use and produce reports and dashboards in preparation for their project.

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