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June 14, 2018
By Trey Johnson
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Data Management,Data Visualization
To explain how data management speeds up the return on investment of data visualization tools, this blog examines three common business scenarios – writes ZAP’s tech evangelist, Trey Johnson. But if you want the ‘espresso version,’ here are those top five ROI enhancements in brief:
Ever tried to pull off a business conversation while speaking a foreign language but with a vocabulary of just ten or twenty words? I doubt it. But, more often than not, business people are asked to ‘converse’ with their organization using tools, data, and language they may not understand in the vain hope of driving a detailed, productive dialogue.
If you’re in IT and feel like you’re struggling to make your organization’s data visualization tools become adopted, embedded and trusted, it might feel like you’re asking your users to communicate in a foreign language.
To define the ways data management provides returns for data visualization, let’s look at three common self-service BI scenarios I’ve often seen:
There are so many highly approachable visualization tools with Power BI, Tableau and Qlik, for example, bringing the promise of ‘self-service.’ What does that mean in practice? Well, often, the organizational view is that “our staff know Excel, so they can pick this tool up, too.”
Yes, in many cases, a subset of staff can get to grips with the product. However, there are also users who become ‘orphaned’ and don’t have the same aptitude. Functional elements, like calculations for example, are not easily picked up by all users. So, while the tools are ‘best-of-breed,’ this isn’t a consolation for users who simply cannot get things done.
Much like the foreign business conversation, a limited vocabulary really hurts in the search for data. The average person uses thousands of words in their vocabulary. Not surprisingly, the average line of business application often has hundreds (if not thousands) of data tables, with a larger multiple of underlying columns of individual details.
The visualization endeavor starts with the user requesting access to a data source. But they almost always get more than they bargained for from that data source. Sometimes they have more complex requirements, in which case they need access to multiple line of business applications/data sources, which further compounds their challenge of getting ‘quickly’ or ‘efficiently’ to the information or insight they need. When there’s a limited ‘vocabulary’ of the data source being accessed with a data visualization tool, rarely does the user have an easy time finding the information they need.
If you look at the first two scenarios, the culmination of them both yields our third: both distraction and potential distortion of the truth. Distraction comes from our basic desire to explore. Exploring isn’t in itself bad, but when it takes a person away from the questions they intended to originally answer, there are clear productivity challenges or simply a concern for people getting ‘lost in the data.’
Likewise, the way the answer is expressed in a self-service visualization tool might look very appealing – the hallowed sexy dashboards! – but this doesn’t mean it is 100% truthful or accurate.
Sometimes it is the semantic of the tool (is the calculation on a row or across all data, for example?) and sometimes it is the lack of user knowledge. Either way, self-service tools simply encourage the development of calculations. Here’s a quick example…
If I build my own personal calculation for profit and show a profit analysis, the consumer of that analysis doesn’t know whether I calculated it at a transaction level to properly factor the item amounts, quantities or cost of goods sold. Maybe the tool I use summarizes and then subtracts the total revenue less a slightly obscured ‘cost’ to generate a less accurate ‘profit’?
The definition of data management by Gartner is “the practices, architectural techniques, and tools for achieving consistent access to and delivery of data across the spectrum of data subject areas and data structure types in the enterprise, to meet the data consumption requirements of all applications and business processes.”
It’s clear that data management is a great companion to self-service BI, specifically, and BI data visualization, generally. The common platform that data management provides puts all self-service users on the same playing field. Each user has their own capabilities but ‘data wrangling’ will not be needed, often resulting in people building confidence with the tools, quickly.
Data management also lets the more knowledgeable personnel in the business construct the ways their data comes together – even across multiple data sources – and supports the preservation of key business logic in calculations.
Data management should offer the ability to use common business vernacular to display data for self-service BI users. No more cryptic table or column names, just the vocabulary the business already knows from the metadata in the business applications they use.
Lastly, data management keeps the user and organization within an environment in which they can efficiently explore and find the answers to their questions. (The better data management environments will also answer the more immediate calculations for them.) And doing so provides the ability to confidently visualize true, accurate data.
Watch this two-minute video for more information on how ZAP Data Hub speed up your ROI on visualization.
Or, for a free, tailored trial of ZAP Data Hub using your own data, enter your details here
Trey Johnson is ZAP’s Chief Evangelist. Based out of Jacksonville, Florida, he joined the company in 2008 bringing experience from leading various boutique BI software and national consulting companies. A published author, speaker, and consultant, Trey sat on the PASS Board of Directors over multiple terms, concluding as their Executive Vice President. He was a long-term member of Microsoft’s BI Partner Advisory Council and has spent the last 25 years delivering business intelligence, data warehousing, and data management solutions to businesses of all shapes, sizes and “data challenges.” Follow Trey on Twitter and LinkedIn.
#Excel for #BI | #Tableau | #PowerBI | #Qlik | #Metadata | #Truth | #StoryTelling | #DataManagement | #DataViz
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