Tag Archives: Analytics

Power BI and Azure DevOps: Reporting “outside the box” to Stakeholders

Microsoft Azure DevOps (ADO) Reporting

With one Power BI report, users have the ability to report against ALL of their Azure DevOps servers and ADO Projects within a single report, and data would be up to date.

Out of the Box Capabilities

For those who need to pull data out of Microsoft Azure DevOps for reporting purposes, there are challenges when attempting to provide that information outside of Azure DevOps.

Typically, if I want to share project reports with my stakeholders, I would provide them a link to share these dynamic dashboards which focus on what they want to see. Project stakeholders may want to see an upcoming production release “bill of health” view, e.g. Burndown chart, Average Velocity, open critical bugs, etc.

However, what if some of your stakeholders don’t have or want access to Azure DevOps? Well, you could take a screen capture of a dashboard, and email your stakeholders that information or…

Power BI to the Rescue

Using both Power BI Desktop, a free license, and cloud Power BI Pro within the Office 365 suite of products, you can create a suite of reports against the Azure DevOps data, and share those reports on a schedule of your choosing. There are also several Analytics / Views that come with Azure DevOps to get you started.

Step 1: Select the Data Source:

Launch Power BI Desktop application found in the Microsoft Marketplace. Select “Get Data” after launching the application. Then a list of data sources is displayed to the user. Select “Online Services” data source group, “Azure DevOps (Beta), then “Connect”.

Power BI Data Source
Power BI Data Source

The user should then be presented with an Azure DevOps login.

ADO Login
ADO Login

Enter your Azure DevOps instance details for connecting to your site. If you are already logged into Azure DevOps in another browser tab, no additional authentication is required. You should now be presented with a list of Analytics / Views that come with ADO “out of the box”.

ADO Analytics Views in Power BI
ADO Analytics Views in Power BI

Just for demonstration purposes, please select the first item on the list, “Bugs – All History by Month”. A preview of the data should be shown on the right side of the panel. Select the “Load” button, which should be enabled if you’ve followed the steps thus far.

On the right side of the screen, there should be a panel called “Fields”. You can select all or some of the columns/fields within the View that was pulled from ADO. As you select the fields, they should populate on the left side of the screen, “Page 1” of the Power BI report. At this point, you may leverage your Power BI prowess to build graphical visualizations of the data you’ve imported.

Power BI Graphical Reports
Power BI Graphical Reports

Save your Power BI report, and then “Publish to Power BI”. The default destination is “My Workspace”, which should be defined with the use of the Power BI Pro, Office 365 app. Save the report and close the Power BI Desktop app. Open the Power BI cloud app from Office 365.

Open the “My Workspace” folder, and look for the “Dataset” and accompanying Power BI “Report” you just created. Click on the “Dataset” with the same name as your report to open it. Select the “Refresh” menu, and the “Schedule Refresh” menu item. Define your schedule to run BEFORE you will push the report via email to your stakeholders.

Subscribe
+ Add new Subscription

Go back to your home screen, select “My workspace”, then select the report you’ve created. Once the report appears, select the “Subscribe” menu. select the menu item “+ Add new Subscription”. Populate the who, what, and when, then select the “Save and Close” button.

Azure DevOps View Creation
Azure DevOps View Creation

That’s it. You could then start to create your own Analytics Views from within Azure DevOps, and then create Power BI reports.

Please note:

“Analytics views are data sets that are exposed to Power BI. You can use views to create reports based on your Azure DevOps data. This feature is in preview. How do I use analytics views?

Popular Tweets from January and February 2018

Tweet Activity Analytics

Leveraging Twitter’s Analytics, I’ve extracted the Top Tweets from the last 57 day period (Jan 1 until today).   During that period, there were 46.8K impressions earned.

Summary:

  • 61 Link Clicks
  • 27 Retweets
  • 86 Likes
  • 34 Replies

Top Tweets for January and February 2018
Top Tweets for January and February 2018

FinTech: End to End Framework for Client, Intermediary, and Institutional Services

Is it all about being the most convenient,  payment processing partner, with an affinity to the payment processing brand?  It’s a good place to start; the Amazon Payments partner program.

FinTech noun : an economic industry composed of companies that use technology to make financial systems more efficient

Throughout my career, I’ve worked with several financial services  teams to engineer, test, and deploy solutions.  Here is a brief list of the FinTech solutions I helped construct, test,  and deploy:

  1. 3K Global Investment Bankers – proprietary CRM platform, including Business Analytics, Business Objects Universe.
  2. Equity Research platform, crafted based on business expertise.
    • Custom UI for research analysts, enabled the analysts to create their research, and push into the workflow.
    • Based on a set of rules,  ‘locked down’ part of the report would  “Build Discloses” , e.g. analyst holds 10% of co.
    • Custom Documentum workflow would route research to the distribution channels; or direct research to legal review.
  3. (Multiple Financial Org.) Data Warehouse middleware solutions to assist organizations in managing,  and monitoring usage of their DW.
  4. Global Derivatives firm, migration of mainframe system to C# client / Server platform
  5. Investment Bankers and Equity Capital Markets (ECMG)  build trading platform so teams may collaborate on Deals/Trades.
  6. Global Asset Management Firm: On boarding and Fund management solutions, custom UI and workflows in SharePoint

*****

A “Transaction Management Solution” targets a mixture of FinTech services, primarily “Payments” Processing.

Target State Capabilities of a Transaction Management Solution:

  1. Fraud Detection:  The ability to identify and prevent fraud exists within many levels of the transaction from facilitators of EFT to credit monitoring and scoring agencies.  Every touch point of a transaction has its own perspective of possible fraud, and must be evaluated to the extent it can be.
    • Business experts (SMEs)  and technologists continue to expand the practical applications of Artificial Intelligence (AI) every day.  Although extensive AI fraud detection applications  exists today incorporating human populated Rules Engines,  and AI Machine learning (independent rule creation).
  2. Consumer “Financial Insurance” Products
    • Observing a business, end to end transaction may provide visibility into areas of transaction risk.   Process  and/or technology may be adopted / augmented to minimize the risk.
      • E.g. eBay auction process has a risk regarding the changing hands of currency and merchandise.  A “delayed payment”, holding funds until the merchandise has been exchanged minimized the risk, implemented using PayPal.
    • In product lifecycle of Discovery, Development, and Delivery phases, converting concept to product.
  3. Transaction Data Usage for Analytics
    • Client initiating transaction,  intermediary parties, and destination of funds may all tell ‘a story’ about the transaction.
    • Every party within a transaction, beginning to end, may benefit from the use of the transaction data using analytics.
      • e.g. Quicken – personal finance management tool; collects, parses, and augments transaction data to provide client  analytics in the form of charts / graphs, and reports.
    • Clear, consistent, and comprehensive data set available at every point in the transaction lifecycle regardless of platform .
      • e.g. funds transferred between financial institutions may  have a descriptions that are not user friendly, or may not be actionable, e.g. cryptic name, and no contact details.
      • Normalizing data may occur at an abstracted layer
    • Abstracted, and aggregated data used for analytics
      • e.g. average car price given specs XYZ;
      • e.g. 2. avg. credit score in a particular zip code.
    • Continued growth opportunities, and challenges
      • e.g. data privacy v. allowable aggregated data
  4. Affinity Brand Opportunities Transaction Management Solution
    • eWallet affinity brand promotions,
      • e.g. based on transaction items’ rules; no shipping
      • e.g.2. “Cash Back” Rewards, and/or Market Points
      • e.g.3. Optional, “Fundraiser” options at time of purchase.
  5. Credit Umbrella: Monitoring Use Case
    • Transparency into newly, activated accounts enables the Transaction Management Solution (TMS) to trigger a rule to email the card holder, if eligible, to add card to eWallet

Is Intuit an acquisition target because of Quicken’s capabilities to provide users consistent reporting of transactions across all sources?  I just found this note in Wiki while writing this post:

Quicken is a personal finance management tool developed by Intuit, Inc. On March 3, 2016, Intuit announced plans to sell Quicken to H.I.G. Capital. Terms of the sale were not disclosed.[1]

For quite some time companies have attempted to tread in this space with mixed results, either through acquisition or build out of their existing platforms.  There seems to be significant opportunities within the services, software and infrastructure areas.  It will be interesting to see how it all plays out.

Inhibitors to enclosing a transaction within an end to end Transaction Management Solutions (TMS):

  • Higher level of risk (e.g. business, regulatory) expanding out service offerings
  • Stretching too thin, beyond core vision, and lose sight of vision.
  • Transforming tech  company to hybrid financial services
  • Automation, streamlining of processes, may derive efficiencies may lead to reduction in staff / workforce
  • Multiple platforms performing functions provides redundant capabilities, reduced risk, and more consumer choices

 Those inhibitors haven’t stopped these firms:

Payments Ecosystem
Payments Ecosystem

 

Searching Big Data for ‘Digital Smoke Signals’ – NYTimes.com

Searching Big Data for ‘Digital Smoke Signals’ – NYTimes.com.

Excellent Article how the Public Sector is transforming by the private sector.  Good read.  Article frames out the group structure, and the team, but doesn’t go into the output of the statistics, i.e. group output, which is disappointing.  Gives you the sense the team is new, and is still coming to grips with what to output, whom to present it, and the advantages presented and opportunities taken as a result of the data. It could be this new, dynamic group within the United Nations is still trying to integrate with the rest of the organization, they are still wresting with the data, or the data draws dangerous conclusions that are not for public distribution.  Give the article a run through, and you will see the subtext is predicting world economies, and that is confidential to the people being analyzed, and also to the people who invest.

Microsoft Business Intelligence Whiteboard Prototype Potential

I just read an interesting article in BBC News – Microsoft unveils self-sketching whiteboard prototype, progressing Microsoft Business Intelligence, and I must concur and disagree with Brian Blau, a consultant analyst at Gartner, and is quoted in the article:

“The metrics have to be tailored for each one of these circumstances and companies are still likely to need experts in their own business to be able to run something like this if it’s to be useful.”

There are already Business Intelligence (BI) Analysts in most mid size to large firms across almost all sectors. These analysts already are creating custom reports using business intelligence tools, and then displaying these reports on multiple mediums.  The prototype, it seems, Microsoft is proposing should expand BI to C suite executives, and also enhance the existing abilities of BI analysts, that is the hope.  It does not seem the article is suggesting the removal of the Business Analysts; however, the hope in the BI world has been to try to get more executives to create dynamic reports, and visualizations.  Although, typically C Suite executives ask their BI Analysts to generate `canned`, defined reports executives can export to their Powerpoint presentations. If this new prototype medium is similar to the intuitiveness Microsoft has recently brought to the table with the Surface, it`s possible we may see more adventurous executives trying to create reports; however, that may create new problems.

Business Analysis typically use a language called SQL, or Structured Query Language, although some BI tools try to abstract that layer, and provide the senior BI analysts or execs the layer of abstraction they can use, and more easily understand.  Unfortunately, in many cases, a performance degredation occurs in generating the reports for any number of reasons, e.g. the executes create reports, which are well-meaning, but the non skilled execs not familiar with the intricacies of analytics, may create non-sensical reports, ie, ask the wrong questions, wastes database, or data warehouse resources, and eventually they get an answer to a question, which they didn`t mean to ask.

So in regards to Brian Blau`s quote, I would tend to agree with him after all, although the question C-Suite executives ask typically: I have all this information and technology, why can`t I access it directly.  Answer: the way the data is stored is typically in a way which requires SQL,  a skill set the C-Suite executives may not have or be very skilled at using.  It`s not the sexyness of the medium that will eventually make this work, although it will make the execs salivate, it`s a layer of abstraction from the complexity of the data, which is easy for anyone to use, and is extremely efficient.  Additionally, are advances in data warehouses which are making the analytical processing faster. We may be there, only time will tell.