4 Common Analytics Reporting Errors to Avoid
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See show how to spot and avoid mistakes in model joins, default aggregation, filtering on aggregates and order of operations that can seriously undermine your reporting efforts and cost your business. These mistakes can hide in any platform. We show demos in Power BI, Cognos and Tableau. See the demos and download this deck: https://senturus.com/resources/4-common-business-analytics-reporting-errors/ Senturus offers a full spectrum of services for business analytics. Our resource library has hundreds of free live and recorded webinars, blog posts, demos and unbiased product reviews available on our website at: https://senturus.com/resources/
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4 Common Analytics Reporting Errors to Avoid
- 1. 1
- 2. 2 Hundreds of resources Visit our Knowledge Center to download this presentation and explore other assets: senturus.com/resources 2
- 3. •Patrick Powers •Data Scientist, Consultant and Trainer Senturus, Inc. •Michael Weinhauer •Director Senturus, Inc. 3 Introductions
- 4. Agenda •Introductions •Issues •Modeling •Aggregation •Aggregate filtering •Order of operations •Senturus overview and additional resources •Q&A 4
- 5. Enjoy the full webinar presentation This slide deck is from the webinar 4 Common Mistakes That Equate to Big Analytics Reporting Errors To view the FREE video recording and download this deck, go to https://senturus.com/resources/4-common-business- analytics-reporting-errors/ 5
- 6. • Bad data? • Aggregation or modeling issue! • This can affect ANY business intelligence tool When data doesn’t tie back 6
- 7. •Field names are labeled the same in different tables, but are generated differently •For example: One table has CUSTOMER_ID and it’s been joined to CUSTOMER_ID in a second table Modeling issue: incorrect joins 7
- 8. •Data at different granular levels •For example, SALES table and a RETURNS table • 1:1 join is probably not going to work •For example, calculating percentages • Average returns per day if you have 31 days of sales, but 17 days of returns? Modeling issue: cardinality 8
- 9. • Default aggregation and different levels of granularity • Upstream modeler may have set it to something different •For example, is UNIT_PRICE a total or an average? • Might require multiple fields (calculated or modeled) to be published in a package Issues with aggregation 9
- 10. • It’s important to know WHEN we are filtering • Row-level or the aggregated-level? • BEFORE or AFTER aggregation filtering •For example, let’s say we have two orders with printers, one with $75,000 in revenue and one with $85,000 in revenue •If we filter REVENUE > $80,000, when we filter it will make a difference •Do we discard the one order for $75,000 or do we show a single aggregated result of $160,000? Filtering on aggregates 10
- 11. • The order in which we do a calculation or a filter can have repercussions • In SQL world, similar to a WHERE clause vs. a HAVING clause • DO THIS FIRST, THEN DO THIS • Known as creating context or defining the solve order Order of operations 11
- 12. Summary • Sometimes the issue isn’t with data, but how the tool is interpreting the data • Look for join and structural issues first • Work with the lowest level of granularity to see the record level detail to determine aggregation issues • Remove filters to make sure the raw results are as expected 12
- 13. Demos •Power BI: Aggregate filter problems •Cognos: Before and after auto aggregation •Tableau: Aggregate filter problems Watch the demos: https://senturus.com/resources/4-common-business-analytics-reporting-errors/ 13
- 14. Additional resources 14 Insider viewpoints Technical tips Unbiased product reviews Product demos Upcoming events More on this subject
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- 21. 21 Join the Senturus team We’re hiring talented and experienced professionals • Senior Microsoft BI Architect • Senior Azure Architect • Modern Analytics Solution Architect • Java Software Engineer See job descriptions: https://Senturus.com/why-Senturus/careers Send your resume to: jobs@Senturus.com
- 22. © 2022 by Senturus, Inc. This presentation may not be reused or distributed without the written consent of Senturus, Inc. www.senturus.com 888-601-6010 info@senturus.com Thank You
Notes de l'éditeur
- The first question we usually get is “Can I get a copy of the presentation?” Absolutely! It’s available on Senturus.com. Select the Resources tab and then Resources Library. Or you can click the link that was just posted in the GoToWebinar Control panel. Be sure to bookmark the resource library. It has tons of valuable content addressing a wide variety of business analytics topics.
- Joining us today is…..Patrick Powers Patrick has 22 years of experience in business intelligence and data analytics. He’s one of our trainers, delivering classes on Power BI, Tableau and Cognos. His certifications include multiple programming languages, including Java and C++, and database certification (MS SQL).
- There are times when data in the report doesn’t seem to tie back to the source data Is it a data issue? Do I have bad data? Typically, the issue isn’t bad data, but rather how the data is being interpreted at a tool level This can affect ANY business intelligence tool Sometimes it’s an aggregation issue, sometimes a modeling issue Let’s review some common issues that can happen
- Incorrect joins A common problem is how data is joined together One table has CUSTOMER_ID and it’s been joined to CUSTOMER_ID in a second table In this case, CUSTOMER_ID in the second table is generated differently from the one in the first table Even though the field names match, no results are returned due to difference in data Again, this isn’t bad data, it’s just different
- Cardinality Cardinality is another common problem especially when dealing with data at different granular levels For example, if you have a SALES table and a RETURNS table, a 1:1 join is probably not going to work as every sale (hopefully!) doesn’t have a return While that’s a clear issue, what about FORECAST or INVENTORY? Here you would expect to have data for every record This can also be an issue when trying to calculate percentages - What if you have 31 days of sales, but 17 days of returns - What’s the average returns per day? Do we divide by 17 or by 31? An outer join may be needed to return all rows to get an accurate number
- Default aggregation can cause issues with different levels of granularity in a report Especially important when trying to move to a self-service environment Depending on the tool, the upstream modeler may have set it to something different – for example, is UNIT_PRICE a total or an average? This might depend on different business needs Might require multiple fields (calculated or modeled) to be published in a package
- When we filter, it’s important to know WHEN we are filtering Are we interested in the row-level or the aggregated-level? For example, let’s say we have two orders with printers, one with $75,000 in revenue and one with $85,000 in revenue If we filter REVENUE > $80,000, when we filter it will make a difference Do we discard the one order for $75,000 or do we show a single aggregated result of $160,000? This is known as BEFORE or AFTER aggregation filtering
- Just like with filtering, the order in which we do a calculation or a filter can have repercussions In the SQL world, this can be similar to a WHERE clause versus a HAVING clause In other words, DO THIS FIRST, THEN DO THIS With different tools, this is known as creating context or defining the solve order
- Data is everywhere and you can create a quick Tableau Dashboard using just about anything. But the old garbage in garbage out principal often applies….And end of the day the data behind your dashboards needs to be accurate, informational and up to date. ??? Good data is an absolute requirement to make accurate projections which in turn drives supply chains and helps people make informed decisions. Today we are really seeing how important good data is.
- Senturus provides 100s of free resources on our website. We have been committed to sharing our BI expertise for over a decade. Go to Senturus.com/resources You can also see recordings of Patrick’s two last webinars: Power BI Builder and Paginated Reports AND Power BI Data Cleansing and Power Query Editor.
- My colleague and Cognos installation and upgrade expert Todd Schuman will walk us through the installation and configuration steps on the server side of Cognos Analytics. Be sure to bring your questions for him to answer. We'll have details on our website soon about our Mar 30 events.
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