Highlights
- Gain an understanding of Data Analysis and Data Science
- Explore Statistical Summary
- Identify Outliners
- Conduct series forecasting using an established suite of methods for time series prediction
- Advanced Analytics Custom Visuals
- Clustering techniques using standard and custom visuals
- Visualise combined KPIs to help you with multi-line chart and labels for current date, values and variances
- Compare different methods of creating visuals based on R and Python
- Use decision trees and decomposition tree to analyse important decision criteria
- Explore the key influence visual
- Use small multiples to allow easy comparison of different parts of your dataset
- Use Anomaly detection features
- Analyse Twitter posts and media impressions with Twitter Analysis tools
- Learn to create 'What If' parameters to dynamically transform your dataOn special request (extra half day) : AI and Power BI: use Azure cognitive services in Power BI
- Text analysis
- Sentiment analysis
- Key feature identification
Course Details
WHAT IF SCENARIOS
- Create “What if” parameters
- Create Dashboard to show effect of parameter variation
- Create Multiple “What if Parameters”
- Combine multiple parameters on a Dashboard
Python and R in Power BI
- Set up Power BI to use Python and R language to create visuals
- Increase your choice of charts using R in PowerBI
- Try different visualizations using Python and R
TIME SERIES FORECAST
- Create forecast based on previous years values using DAX
- Create projected forecast using Line chart
- Create projected forecast in ARIMA using Python
KEY FEATURE ANALYSIS
- Analyse what are the key features that influence your returning customer
- Analyse what are the key features that influence your employee leaving
COMBINED KPI
- Visualize combined KPIs
- Analise the relative variance of combined KPIs
- Show the single components of the combined KPIs
ERLANG ALGORITM
- Create a call centre staffing tool to calculate the number of staff required to meet your SLA level
DECISION TREE
- Analyse whether your employees are prone to leave or not using a decision tree
Apply Advanced Power BI Analytical Techniques
- Anomaly detection
- Discover anomalies in your data: unusually high or low records
- Cluster analysis
- Outliner detection
- Cross sell opportunities
- Pattern recognition
- Customer segmentation
- Pareto rule
- Dynamic ranked list
- Decomposition tree (see December summary)
TWITTER ANALYSIS
- Import tweeter feeds
- Time line visual for twitter posts
- Word cloud analysis with custom visual
- Word cloud analysis with Python
- Life connection stream to tweeter feeds
- Create sentiment analysis using Azure Cognitive systems
- Import tweeter feeds
- Time line visual for twitter posts
- Word cloud analysis with custom visual
- Word cloud analysis with Python
- Life connection stream to tweeter feeds
- Create sentiment analysis using Azure
Who should attend
This course is aimed at delegates who feel comfortable using Power BI's basic features and who are looking to take the tool to the next level of Data Analysis and who would also like to get a gentle introduction to Python.
Feedback
4.8 out of 5 average
" I enjoyed the depth that we covered analytical techniques such as anomaly detection and cluster analysis, whilst improving my knowledge on DAX and KPIs. "BC, Performance analyst, Data Analysis with Power BI, May 2023
Watch live client feedback from Data Analytics courses:
“JBI did a great job of customizing their syllabus to suit our business needs and also bringing our team up to speed on the current best practices - very impressive” Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2024
