Learn big data analytics directly in Excel 2010 or 2013.
Power Pivot is free Excel add-in developed by Microsoft. It is designed to deal with large complex data sets. No programming required!
Always working on real examples - the course is specifically based on real world use cases. No long slides, but rather hands on examples. All material used in lectures is available for download. Students are highly encouraged to experiment with data themselves.
Comprehensive assignments will be available after each section. These will let you check newly acquired knowledge in practice.
At any time I will be available to answer questions or simply discuss some interesting topic.
At the end of the course you will feel comfortable in multiple areas:
Taking into account exercises and assignment, course could be completed in a ~4 days 2-3 hours per day.
Let's get ready for era of big data.
Let's talk a bit about how the learning will take place. Some tips to even better understand the topics.
Here are the data used later in the course. If you consider recreating example yourself or just trying things out - please download these files and find file you are interested in.
Good luck crunching big data!
Installing Power Pivot is a breeze:
Power Pivot comes pre-installed with Office Professional Plus or Office 365. However, it should be still enabled:
Data analyst with more than 3 years of experience.
Employing various tools for data analysis. Always picking the right tool to do the job. I use R package often combining it with Excel, SQL databases and Access on daily basis.
Graduated econometrics from Vilnius University faculty of Mathematics and Informatics. Afterwards I worked as economical forecaster. Currently my position being analyst of online advertising data in leading advertising platform - focusing on insights from large datasets.
I am constantly participating in events/conferences regarding data analysis. Currently interested in open data initiatives - possibilities to open up more government data for public use. Participating in contests of predictive analytics.
Let me know if you have any questions/suggestions regarding data and analysis. You can find my on Google+ or Linkedin.