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Alteryx
Alteryx

Tableau and Power BI have taken the Enterprise by storm: disrupting legacy vendors who can’t match the ease of use and depth of functionality of these popular analytic toolsets.

 

Yet, as the popularity of such environments continues to grow, there’s a danger that — left unchecked — viral success can turn into longer-term organisational chaos: dashboards, reports and visualisations don’t get properly classified or organised and critical enterprise intelligence isn’t used effectively.

 

Alteryx Connect is a collaborative data cataloguing and discovery solution for the enterprise that changes how information workers discover, prioritise and analyse all relevant information.

It’s a single point of entry into the world of data and business assets, including the vast and valuable resources from modern BI and visualisation tools.

 

Alteryx Connect presents assets from multiple source systems or BI platforms in a single, coordinated view. Users searching for a report or workbook can find exactly what they need, irrespective of which system hosts this content.

 

When formal descriptions and user annotations, clear ownership and traceability through data lineage and business terminology all come together in a single view, it’s fundamentally easier for analysts, report consumers — anyone who works with data — to find what they need, and trust what they find.

 

"I run an Enterprise deployment. We have more than 71,000 named users and as of today 354 Workbooks across 31 Projects on the Production Server."

-- https://community.tableau.com/thread/182442

 

In larger deployments, it’s hard for an analyst to know where to start: which resources to use, which assets are trusted and relevant. Analysts may find themselves with competing versions of standard dashboards — knowing which one to use can make or break the insight that needs to be gathered.

 

Despite having dedicated and passionate software communities, analysts often must make these important decisions in isolation: without context and without the tribal knowledge of their organisation to guide their thinking.

 

"In general we have learned through hard experience that it is wise to have deployed only the lowest number of Projects that constitute enough. You should want to avoid unnecessary proliferation of Projects..."

-- https://community.tableau.com/thread/182442

 

In this post, we provide three key approaches to harness the enormous power, reach and velocity of self-service BI tools and align this content within a collaborative social platform for data discovery.

 

  • For analysts, we’ll show you how to find the best data, reports or analytic content from your organisation’s databases and BI servers.
  • For the C-Suite, we’ll enable your teams to answer the big questions with the best quality assets, without resorting to duplicating data or reports. We’ll also make sure that you’re protecting your customers and their data at all times.

 

 

Tip 1: Keep it Simple!

 

Provide an interface that’s slick, fast and intuitive: design your social data catalogue for maximum engagement and user retention.

 

The reason that Tableau and Power BI Server have stormed the BI market is that the tools are friendly, visual and easy-to-use.

 

Your data catalogue needs to follow these same guidelines — the process to discover and understand terms and resources needs to be ‘Google-like’ in its simplicity: search-find-share-repeat across all the data in a single search.

 

When users enter their search terms, they need to understand in a single glance what assets have actually been returned: is it a business glossary term? Is it a Tableau dashboard, a PowerBI report or an Alteryx workflow? Is it a column in a data store? Clean, simple icons guide the way, making it easy to understand the types of data, with search rankings indicating relative importance: the closer to the top, the more relevant the asset.

 

Search made simple: assets, reputation and trust at-a-glanceSearch made simple: assets, reputation and trust at-a-glance

 

Once a user finds a report, they’ll want to understand it at-a-glance: business meaning and related terms giving that context. Most importantly, they’ll want to be able to access (or request access) to the content in a single click — allowing them to get on with their job with the minimum of effort.

 

Analytics users are naturally social, and as they discover more relevant content are likely to want to give back and improve their community. Social feedback can be given from the context of any asset, without leaving a page: a thumbs-up, a comment or a share is simply a click away — amplifying how others find value and producing a virtuous cycle across an organisation.

 

All this engagement leads to wider adoption of social data catalogues compared to more static, legacy approaches. Value that’s been created in dashboards, workflows and reports gets surfaced more widely and more frequently — giving greater visibility to real enterprise assets (and their authors).

 

"The 'governance' rules are going to matter a whole lot more than any features of Tableau Server.  With no rules, chaos will reign no matter how the Server is Administered.  Don't ask me how I know. :-)"

-- https://community.tableau.com/thread/131184

 

Engagement also provides more relevant audit data: who’s interested in concepts or analytic content. Let this real-world usage drive better governance and availability of your BI environments, keep analytic servers organised and relevant to your data strategy by regularly reviewing usage and community activity.

 

Steps to success:

 

  • Ensure that stewardship or ownership of Tableau or Power BI content is populated from the BI Server — this makes conversations around context and trust much easier.
  • Engage the Chief Data Office to provide certified data assets to complement user-feedback on each item in the catalogue.
  • Motivate users and owners to collaborate and ‘act socially’ to raise their professional profiles.

 

 

Tip 2: Provide a Business Glossary

 

Maintain a repository of standard and trusted definitions across your organisation.

 

Standardised definitions are vital for users to understand and communicate business terms and key performance indicators in a clear and consistent way.

 

Having a repository and definition of standard terms leads to a clear, auditable trail from governed metrics through to associated assets. By creating a business glossary, it’s possible to bridge the most painful gap in most organisations: communication between IT and Business teams. The glossary then evolves to become a centralised dictionary of a company’s common language.

 

A modern business glossary is far more than just a static list of terms. Definitions, data connections, reports and workflows are hyperlinked across a fully-explorable platform. Curate terms into folders based on natural hierarchies. The glossary is the core framework that makes content findable for the organisation — it allows the novice and the analytic expert to work together through common terms.

 

A sample from a Business Glossary within Alteryx ConnectA sample from a Business Glossary within Alteryx Connect

 

Leading companies use business glossaries and modern BI platforms in many inventive ways. Try to reduce the friction between business and BI teams by collaborating over new dashboard requests with the help of a business glossary. Use shared, certified and well-understood terms to make sure developers understand exactly what’s needed in order to maximise business value in a new report or visualisation.

 

Steps to success:

 

  • Treat a business glossary as a foundation for quality and understanding for higher-value analytics.
  • Ingest existing data dictionaries automatically into Alteryx Connect, loading titles, descriptions and folders for organising this information. Create additional definitions directly within Connect as easily as editing a blog post!
  • Create Once — Reuse Often: Define key terms just once in a business glossary and link this definition to all the assets that use it, rather than rewriting the definition in each asset.
  • Keep these definitions alive through an active community of editors/contributors who make annotations and additions to the glossary over time.
  • Use the Chief Data Office to certify/watermark key assets as trusted enterprise resources, and encourage general community feedback on useful definitions and terms.
  • Make assets discoverable by linking glossary terms with content from BI platforms such as Tableau or Power BI, Alteryx Server or enterprise data sources and files.

 

 

Tip 3: Build Trust - Provide Lineage to Data Assets

 

Provide context for your users on how data moves through analytical systems.

 

"I have around 75 Data Sources in my Tableau Server, but i want to know how these sources are built..."

-- https://community.tableau.com/thread/131184

 

"How can I see the path to the data source from a Power BI report (web version, not desktop)? I am able to see the file name listed in the "view related", but how do I tell the directory/path this file is coming from?"

-- https://community.powerbi.com/t5/Service/Finding-the-Data-Source/m-p/262013/

 

Once an analytic dashboard from Tableau or Power BI Server has been discovered, the next question is nearly always ‘can I trust the data flowing into this asset’? Without clear data lineage, it’s hard to understand sources, quality, and the steps of the information supply chain between a report and its origins.

 

The data lineage between Alteryx workflows, databases and PowerBI dashboard contentThe data lineage between Alteryx workflows, databases and PowerBI dashboard content

 

Data and visualisation engineers need to see a high-level snapshot of inputs and outputs in order to trace the flow of data between components: sometimes from an underlying database, sometimes from a repeatable workflow, even from local or networked files. It’s vital that, for each asset uncovered as part of this lineage, there is a drill-down into related terms, data sources, owners and other relevant data.

 

Whereas data lineage gives us descriptive analytics around the current flow of information through data and BI platforms, the same interactive view also enables valuable prescriptive analytics that help us understand future actions.

 

A simple adjustment to a file or data table can ripple through workflows and into business-critical dashboards, causing data or application errors or adversely affecting business decisions.

 

Alteryx Connect helps BI or technology teams understand impact analysis prior to making change happen, and then socialise and discuss these changes with business users via a common language and visual lineage.

 

Steps to success:

 

  • Load metadata into the data catalogue from multiple sources, with Alteryx Connect automatically handling the identification and linking of common assets (such as data sources) to build a rich, connected metadata graph.
  • Explore the relationships between assets and concepts using Connect’s Nexus graph viewer: expand assets to understand lineage and impact analysis.
  • Drill-down into the catalogue for any linked asset: see ownership, social reputation and community conversations for any step in the information supply chain.
Nick Jewell
Alteryx Product Evangelist

Nick Jewell is an official Alteryx evangelist! Starting his career with a Ph.D. in Chemoinformatics (Data Science for Drug Design) helped develop a life-long passion for applied analytics. As a long-serving analyst, architect and innovation leader for Analytics & BI at a large international bank, Nick helped define and implement large scale big data, analytics and informatics solutions at the petabyte scale for global audiences. Nick has a passion for open data, connectivity and emerging technologies in the data and analytics space and is a strong supporter of agile-led and user-centric design.

Nick Jewell is an official Alteryx evangelist! Starting his career with a Ph.D. in Chemoinformatics (Data Science for Drug Design) helped develop a life-long passion for applied analytics. As a long-serving analyst, architect and innovation leader for Analytics & BI at a large international bank, Nick helped define and implement large scale big data, analytics and informatics solutions at the petabyte scale for global audiences. Nick has a passion for open data, connectivity and emerging technologies in the data and analytics space and is a strong supporter of agile-led and user-centric design.