<img height="1" width="1" src="https://www.facebook.com/tr?id=152309752858854&amp;ev=PageView &amp;noscript=1">

Power BI: Top 3 considerations for successful events analytics

Power BI is Microsoft’s premier data analytics tool for business intelligence (BI) and a game changer for creating powerful, interactive visualisations and live dashboards without having to be a designer.

Interactive data analytics tools like Power BI turn complex calculations and dry numbers into something accessible and engaging, thanks to a wide range of easy-to-digest visual elements like charts, graphs, and maps to enable more holistic insights for events and venue operators.

It also can not only bring together your key data from disparate sources in both the cloud and on-premises, but track and report the metrics that matter most to your business and provide a real time picture that consolidates customer demographics and financial and operational results.

In this article, Xello’s team of data experts share their extensive knowledge to outline the top 3 high-level business considerations before you can begin successfully using Power BI for events and venue analytics.

Understand your data sources and pull them into a central repository


Before you look into data visualisation for insights into your events, understand what and where data sources are.

It’s safe to say the majority of organisations have multiple islands of data (data stores) across their cloud and on-premises environments. Forrester revealed out of 74% of businesses striving to be “data-driven,” only 29% succeed at properly centralising their data, refining it for analytics and producing real insights.

Disparate sources makes it harder to access, share and analyse anything, so before you can think of using Power BI to visualise your venue data, you have to do some heavy lifting, and identify and organise where everything is first.

  • Cloud, on-prem or hybrid?: Where is your business-critical historical data currently stored? Is it spread out in the cloud, on-premises or both? Ensure you know exactly where your most important data is spread out so you can bring it all together with the right solution based on your current setup.
  • What type of business data?: Determine the types of business data (machine data, master data, qualitative data, metadata, market research, customer data, transactional data, etc) you collect, store in databases and can be processed for data insights. Whether it’s generated by your events website, point-of-sale systems for sales, types of personnel, stock control, staff rosters and timesheets, get it ready for consolidation.
  • Data quality: Assess the consistency and quality of your data - is it raw, structured summary, metadata, unstructured? The quality of your data will influence what type of warehousing solution you need before you can even use Power BI for visualisation.

It’s crucial to know what data sources you have, the quality and environments they’re currently stored in, and what information is most relevant from each store. Without this level of assessment, the data you pull into Power BI may not be as reliable or relevant as desired - and it'll be harder to glean insights or pinpoint true events performance.

Businesses can use API calls to pull their most relevant and reliable data into a central repository, where it is stored and eventually used as a data source for Power BI. These are referred to as data warehouse solutions - learn why cloud-based data warehouses help consolidate, structure and send reliable data for use in your Power BI reports.


Identify the most important metrics to visualise to make better decisions


As cloud technology matures and digital transformation accelerates, data visualisation plays an increasing key role in delivering the metrics, trends and insights businesses need. However, leveraging Power BI’s data visualisation capabilities only works if your decision-makers identify the right metrics to visualise in your dashboards.

A great data report starts with a plan, so examine the data you have to work with, define your business needs, how your data will be used and which industry-specific metrics are most relevant to visualise for your users.

For venues, stadiums, retail and events management, consider:

  • Age and gender distribution
  • Cost of goods
  • High value transactions (by day, ticket type, event type, etc)
  • Financial KPIs
  • Patrons entering
  • Payment type
  • Staffing
  • Stock control
  • Venues leasing
  • Web analytics (social media interactions, web purchases)

Once you pinpoint which data to use and have it ready in the right data warehouse solution, Power BI can cleanly and efficiently consolidates all relevant data and present it with rich visuals, spread across multiple live dashboards which update in real-time. These reports can then be used to monitor, track, predict, measure, manage and test to answer the business questions that drive your data analytics design and desired outcomes.

Events, retail and venue operators that need to view complex datasets such as customer demographics, financial results, operational efficiency and social media interactions can easily split this data into four distinct dashboards and consolidate the most important metrics of each category into one ‘main’ event dashboard, with the most important visualisations at the forefront.

For example, your key business considerations to answer with Power BI might be:

  1. What is the total ticket sales and which part of the venue have they sold?
  2. Is there sales growth or decline for specific events at my venue?
  3. What is the historical ticket sales performance and trends?

Power BI can help you drill down on the trends in ticket sales by filtering data by venue, region, season and many more custom-set parameters, which you can click on a dashboard to dynamically change what data is represented on an interactive map of the venue. The same report can also measure how many items or tickets have been sold so far, and plot heat maps to the parts of the venue where patrons enter and where sales are strongest.


A separate dashboard can present data that specifically measures historic performance (current and previous ticket sales) and include financial KPIs that trigger alerts when reached, and a predictive trend graph that updates how ticket sales increase or decline over time per event.

Another dashboard can consolidate and present key web analytics such as top shared posts, likes and retweets, web purchase details and payment type to enable better target marketing campaigns which can help you hone in on the most profitable market segments.


Build a cloud platform that can scale with your data volume


Power BI is just one of the many services and technologies part of the broader Microsoft Azure package. It leverages the scalability of the cloud to dynamically scale with each business’s unique data volume needs, and includes native integration with other key data services such as:

  • Azure Data Lake: A scalable central data storage repository that holds large amounts of data in its original format until it is needed for operational preparation (data warehouse) and exploratory analysis (Power BI). Read our guide on Azure Data Lake here.
  • Azure Data Factory: Helps businesses create data-driven workflows to ingest data across cloud and on-premises environments, prepare the data for further use, and deliver trusted data to data warehouse that can be turned into meaningful and valuable information with Power BI. Read our guide on Azure Data Factory here.
  • Azure Data Warehouse: Sorts all data collection and distribution, backup and recovery planning, metadata management, cleansing and transformation to further categorise and prepare it for reliable analytic consumption by Power BI. Read our guide on ADW here.

With these powerful tools, Azure is an ideal cloud platform for businesses with large, disparate datasets that need to be consolidated, prepared and used for reliable analytics with Power BI.

The fact is managing and storing data on traditional on-premises infrastructure is only growing harder and slower to handle by the day, often taking days or weeks to install and run servers.  

Azure Platform as a Service (PaaS) and its infinite resources enable your business to have databases set up and natively integrated with Power BI more efficiently, so you don’t have to worry about traditional physical servers being unable to handle volume, unforseen incompatibilities and you can focus on gathering better venue insights.


Using Power BI for venue analytics: Key takeaways

Users have significant control over how data is extracted and presented with Power BI.

Visualisations give greater context and impact than traditional static reports, and your venue management team can look up business performance trends from anywhere and make more strategic decisions with up-to-date data. Extensive integration means you can share it faster using Dropbox, Google Drive, OneDrive and other applications.

However, only once you take the time to assess, prepare and understand the business needs and metrics you need to have can you pick the right visuals to tell the story you need to extract actionable insights from your venue data. 

Not clear on where to start? It's always recommended to do a Power BI PoC and source expert consultation before jumping into any data analytics initiative.

Brush up on the 4 Best Practices for Successful Business Intelligence with our downloadable guide - get your free whitepaper today.

Tags: Data Analytics, Power BI, Data & AI