(MENAFN- EIN) Unilytics, a Tableau partner who offers Tableau dashboard training & consulting, has listed their top tips for improving the performance of Tableau dashboards. TORONTO, ONTARIO, CANADA, May 5, 2019 / EINPresswire.com / -- Unilytics, a Toronto based Tableau partner who offers Tableau training and consulting services, has shared the ultimate checklist of 30 recommendations for enhancing tableau dashboard performance. Unilytics has been offering Tableau training services at all levels to their clients for over 6 years and has built upwards of 1200 Tableau dashboards!

In a world where two-second response times can lose an audience, performance is crucial.
Unilytics' checklist is designed to optimize the performance of the user's Tableau Dashboard. That includes the speed of data analysis as well as the speed of loading views or dashboards that you access on your desktop or from Tableau Server.

It should be noted, that not all of these tips will work for all situations. In order to make sure that your dashboard is working as best as it can for you, it is of course recommended that you have some experience in dealing with Tableau dashboards and have a basic understanding of the data set you're using. Then you will be able to evaluate what tips and tweaks will work best for your specific use case.

The list below is presented in order from 'most impactful' to 'least impactful', in terms of how much they can affect your Tableau dashboard. It should be noted again that just because one of the tips below can be the most impactful on a Tableau dashboard, doesn't necessarily mean that it will be with yours. Every Tableau dashboard is different, and based on the data that you're analyzing, you may have different results when implementing the suggestions below.

Unilytics' List of Tableau Dashboard Performance Improvements:

• Consider offloading data preparation/cleansing from Desktop and into Prep
• Extract source data and consider using a multi-table (i.e., normalized) extract, where appropriate, but especially for multi-fact tables (e.g., survey data, snowflake schemas, etc.)
• Reduce number of marks in visuals (i.e., aggregate source data, aggregate views, etc.)
• Remove/hide unused columns
• Pivot columns to rows where appropriate (e.g., date columns like months or years, survey responses)
• Reduce number of rows
• Reduce size of large text table views
• Connect to data sources using native drivers rather than ODBC
• Avoid using custom SQL (this bypasses Tableau's ability to generate efficient, optimal queries)
• Reduce number of views per dashboard
• Reduce number of filters on views
• Promote 'high impact' 'frequently used' filters to context filters
• Replace LOD filters with sets that are formula-based
• Determine where performance issues exist (i.e., Desktop Only, Server Only, or both) and address accordingly, consider using a performance recording for low-level detail of performance factors
• Use only one or two context filters, and only if they reduce record count by 10% or more
• Change enumerated filters (e.g., dropdown, radio, slider) to unenumerated filters (e.g., custom value list, wildcard match)
• Avoid excessive use of 'only relevant values'; filters
• Reduce number of text fields
• Avoid sparsely populated data sources (e.g., lots of NULL/blank values), unless the data is extracted
• Use joined data sources instead of blended data sources when data sources have high number of records (i.e., not as useful if one data source is 'reference data' with very few rows and the other is 'fact data' with lots of rows)
• When joining tables, use the minimum tables and joins necessary to generate the data you need
• When possible, avoid linking blended data sources on long text fields, or fields with high cardinality (i.e., lots of unique values)
• Avoid string manipulation where possible (e.g., FIND, LEFT, RIGHT, MID, etc.)
• Allow logins to database ability to create and delete temp tables
• Use optimal date functions (e.g., DATETRUNC, DATEADD, DATEDIFF) rather than complex conditional logic
• Use the most efficient type of calculation: table calculation, level of detail expression, aggregate expression, row-level expression
• Use fastest possible data type (e.g., integers and boolean are faster than strings and dates)
• Use optimal aggregation (i.e., MIN and MAX are more efficient than ATTR or AVERAGE are, COUNTD is one of the slowest of all aggregations)
• Optimize use of external calculations (i.e., Python, R) if they are absolutely required
• Use fixed sizes for dashboards

These tips and suggestions are valuable for both new and advanced users, though they will have different effects for everyone based on the data being analyzed. If you're finding the suggestions aren't giving you the result that you'd like, or if you're having trouble with your Tableau Dashboard and would like to learn more, please reach out to Unilytics for Tableau training.

About Unilytics:
Unilytics has been a leading business analytics company since 2001, offering products, consulting and training to over 800 customers in a wide variety of business sectors and government. Unilytics specializes in helping clients put complex information into a form that will quickly and clearly reveal opportunities and actions to improve their business performance.
Unilytics sells Tableau licenses and provides comprehensive BI CONSULTING & TRAINING SERVICES including: BI strategy, KPI assessment, data preparation, Tableau dashboard creation, Tableau Training, and Tableau server implementation and configuration.
To learn more, please visit their website at www.unilytics.com .
Unilytics
www.unilytics.com
+1 416-441-9009
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