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Power BI Data Analysis training course

Analyse and present your data using Power BI and Python - A first step into Data Science

Next 28 September (Remote)
2 days £1495 + VAT

JBI training course London UK

  • Gain an understanding of Data Analysis and Data Science
  • Learn to create 'What If' parameters to dynamically transform your data
  • Explore time series forecasting using an established suite of methods for time series prediction
  • Acquire skills in key feature analysis to extract data, create datasets, and transform and visualise data
  • Take a sample of your data (in excel or csv format) and learn to apply algorithms
  • Visualise combined KPIs to help you with multi-line chart and labels for current date, value and variances
  • Apply Erlang for calculating the number of agents or staff that you need in a call centre or in your team
  • Compare different methods of creating visuals based on Data Analysis and Machine Learning, R and Python
  • Use decision trees to analyse important decision criteria for your employees
  • Analyse Twitter posts and media impressions with Twitter Analysis tools

FULL COURSE DETAILS

Our Power BI Data Analysis training course is aimed at delegates who want to get more out of their data using a combination of Power BI's inbuilt tools and simple DAX and Python coding to help with more complex data analysis and predictive modelling tasks.

This is a gentle introduction to Data Analysis and Data Science and should appeal to the more adventurous Power BI users, who need to step up a level, without the need for a formal Data Science background.


The course is a fully hands-on, 100% practical one in which you will test different ways of analysing your data to answer questions like: What are my forecasted sales for next year? Why are employees leaving?  What is the ideal staff number for my call centre? How can I analyse sentiment on Twitter posts?

A simple scenario that may be covered on the course is visually displaying how to predict your profit if sales increase. “What If” parameters allow you to create different scenarios in which you can dynamically change the value of one parameter and see the effect of this change on your measure.

You will compare different methods of creating visuals based on Data Analysis and Machine Learning, R and Python. You will create a visual that explains the key factors that influence your clients to come back... And many other case scenarios.

You can also take a sample of your data (in excel or csv format) and apply algorithms.


FULL COURSE DETAILS
JBI training course London UK
JBI training course London UK

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.


FULL COURSE DETAILS

Related Courses

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 suing 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 
 
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CONTACT
+44 (0)20 8446 7555

enquiries@jbinternational.co.uk

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