Abstract: In today’s data economy and disruptive business environment, data analysis with user friendly visualization is vital for professionals and companies to stay competitive. Data Analysis and developing interactive visualizations which provide insights may seem complex for a non -data professional. That should not be the case, thanks to various BI & data visualization tools. Tableau is one of the most popular one and widely used in various industries by individual users to enterprise roll out.
In this complete hands-on training session, you will learn to turn your data into interactive dashboards, how to create stories with data and share these dashboards with your audience. We will begin with a quick refresher of basics about design and information literacy and discussions about practices for creating charts and storytelling utilizing best visual practices. Whether your goal is to explain an insight or let your audience explore data insights, using Tableau’s simple drag-and-drop user interface makes the task easy and enjoyable.
In this session, we’ll cover intermediate and advanced tableau functionality:
1. Database connectivity
2. Blending and joins using multiple data sources, web connectors and plugins,
3. Perform data analyses and create graphs from a real-world dataset, using Tableau Public (free to use)
4. Deeper Analysis – Trends, Clustering, Distributions, and Forecasting
5. Table Calculations, Sets, Filters, Level of Detail expressions, Parameters
6. Spatial analytics - Using Maps and Geocoding
7. Right and Wrong way to build Dashboards and Best Practices
8. Design for Mobile consideration
9. Tableau workflow for enterprises – how to roll it within your enterprise
10. Examples of Tableau Stories and Dashboards best practices + Tips
b. Dashboard Objects
c. Choose Five or Fewer Colors for Your Dashboards
d. Common Charts to use
e. Include Comparisons for data – time series (annual, quarterly, etc)
f. Use Segmentation for visuals
g. Design Tips for Enhancing Your Visualizations
h. Creating Efficient Workbooks
i. Make Beautiful Charts and Advanced ones - Waterfall, Pareto, etc
11. Tableau and R,Python Integration
a. Prediction with R and Tableau Using Regression
b. Decision trees in Tableau using R
You will gain skills to analyze and visualize complex data sets with ease and minimum programming. In short, you will be guided using data sets to build a compelling and convincing story. You will build those stories during the session with best visual practices. This session is for anyone who works with data and is interested in building dashboards and communicate insights about data with stories.
● Tableau Public and Tableau 14 day trial for R and Python for Integration
Bio: Nirav Shah is the Founder of OnPoint Insights, data analytics, software services, and staff augmentation consultancy based in Boston. He has 15 years of industry experience - mainly in consulting on data analytics, big data modeling, process analytics, and real-time data solutions, and training customers in data analytics, dashboards, and data visualization.
He consults and teaches in applying data analytics for manufacturing, operations, supply chain, process control strategies with clients to improve the manufacturing process and operational efficiency. He has implemented real-time process monitoring data analytics and fault detection systems for leading biopharma customers and clients from other industries such as chemical, pulp, and paper, food and beverages. He helps customers in providing better process insights using data-driven solutions.
He is also an Adjunct Professor at the University of Massachusetts in Boston where he teaches Engineering Process Analytics, a graduate-level class in the Engineering Department, teaches Business Analytics and Dashboard Visualization at a technical college and conducts BootCamps and Workshops at General Assembly Boston. He has taught courses and conducted workshops to industry clients on Multivariate Data Analysis for ten years. He has spoken at various conferences ( ODSC East Boston, ODSC India, Global AI).
He completed his dual Masters in Chemical and Computer Engineering from the University of Massachusetts and an MBA in Entrepreneurship from Babson College.