4 Common Analytics Reporting Errors to Avoid

Editor's Notes

• #3: 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.
• #4: 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).
• #7: 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
• #8: 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
• #9: 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
• #10: 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
• #11: 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
• #12: 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
• #13: 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.
• #15: 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.
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