Tag Archives: Azure

Microsoft’s Azure DevOps – Planning Poker Estimation Tool

Although I’ve been a huge fan of PlanningPoker.com since 2011, my Scrum Product team consisted of more than five members, and their Free Membership allows up to 5 users. The team I was working with had just started their agile transformation and was trying out aspects of Agile / Scrum they wanted to adopt. They weren’t about to make the investment in Planning Poker for estimations quite yet, so I stumbled across an estimation tool as a free add-on to Azure DevOps.

Microsoft’s Azure DevOps solution is both a code and requirements repository in one. Requirements are managed from an Agile perspective, through a Product Backlog of user stories. The user story backlog item type contains a field called “Story Points”, or sometimes configured as “Effort”.

Ground Rules – 50k Overview

All team members select from a predetermined relative effort scale, such as Tee Shirt Sizes (XS, S, M, L, XL) or Fibonacci sequence (0, 1/2, 1, 2, 3, 5, 8, 13, 21, 34…) All selections of team members are hidden until the facilitator decides to expose/flip all team selections at once. Flipping at once should help to remove natural biases, such as selecting the same value as the team tech lead’s selection. After that, there’s a team discussion to normalize the value into an agreed selection, such as the average value.

Estimate New Session

Integration with Azure DevOps

The interesting thing about this estimation tool is you can explicitly select stories to perform the effort estimation process right from the backlog, and in turn, once the team agrees upon a value, it can be committed to the User Story in the Backlog. No jumping between user stories, updating and saving field values. All performed from the effort estimation tool.

Time Lock Access: Seal Files in Cloud Storage

Is there value in providing users the ability to apply “Time Lock Access” to files in cloud storage?  Files are securely uploaded by their Owner.  After upload no one, including the Owner, may access / open the file(s).   Only after the date and time provided for the time lock passes, files will be available for access, and action may be taken, e.g.  Automatically email a link to the files.  More complex actions may be attached to the time lock release such as script execution using a simple set of rules as defined by the file Owner.

Solution already exists?  Please send me a link to the cloud integration product / plug in.

The Race Is On to Control Artificial Intelligence, and Tech’s Future

Amazon, Google, IBM and Microsoft are using high salaries and games pitting humans against computers to try to claim the standard on which all companies will build their A.I. technology.

In this fight — no doubt in its early stages — the big tech companies are engaged in tit-for-tat publicity stunts, circling the same start-ups that could provide the technology pieces they are missing and, perhaps most important, trying to hire the same brains.

For years, tech companies have used man-versus-machine competitions to show they are making progress on A.I. In 1997, an IBM computer beat the chess champion Garry Kasparov. Five years ago, IBM went even further when its Watson system won a three-day match on the television trivia show “Jeopardy!” Today, Watson is the centerpiece of IBM’s A.I. efforts.

Today, only about 1 percent of all software apps have A.I. features, IDC estimates. By 2018, IDC predicts, at least 50 percent of developers will include A.I. features in what they create.

Source: The Race Is On to Control Artificial Intelligence, and Tech’s Future – The New York Times

The next “tit-for-tat” publicity stunt should most definitely be a battle with robots, exactly like BattleBots, except…

  1. Use A.I. to consume vast amounts of video footage from previous bot battles, while identifying key elements of bot design that gave a bot the ‘upper hand’.  From a human cognition perspective, this exercise may be subjective. The BattleBot scoring process can play a factor in 1) conceiving designs, and 2) defining ‘rules’ of engagement.
  2. Use A.I. to produce BattleBot designs for humans to assemble.
  3. Autonomous battles, bot on bot, based on Artificial Intelligence battle ‘rules’ acquired from the input and analysis of video footage.

G.E. Plans Big Entry into IoT, Providing Analytics and Predictive Rules

G.E. Plans App Store for Gears of Industry

The investment of $500 million annually signals the importance of the so-called Internet of Things to the future of manufacturing.

G.E. expects revenue of $6 billion from software in 2015, a 50 percent increase in one year. Much of this is from a pattern-finding system called Predix.  G.E. calls its new service the Predix Cloud, and hopes it will be used by both customers and competitors, along with independent software developers. “We can take sensor data from anybody, though it’s optimized for our own products,” Mr. Ruh said.

[Competitive solutions from IBM, Microsoft, and Google] raises the stakes for G.E. “It’s a whole new competition for them,” said Yefim Natis, a senior analyst with Gartner. “To run businesses in a modern way you have to be analytic and predictive.”

G.E. is running the Predix Cloud on a combination of G.E. computers, the vast computing resources of Amazon Web Services, and a few [local] providers, like China Telecom.

China, along with countries like Germany, [are] sensitive about moving its data offshore, or even holding information on computers in the United States.  
The practice of “Ring fencing”  data exists in dozens of jurisdictions globally.  Ring fencing of data may be a legal and/or regulatory issue, that may inhibit the global growth of cloud services moving forward.

Source: G.E. Plans App Store for Gears of Industry

People Turn Toward “Data Banks” to Commoditize Purchase and User Behavior Profiles

Anyone who is anti “Big Brother”, this may not be the article for you, in fact, skip it. 🙂

The Pendulum Swings Away from GDPR

In the not so distant future, “Data Bank” companies consisting of Subject Matter Experts (SME) across all verticals,  may process your data feeds collected from your purchase , and user behavior profiles.  Consumers will be encouraged to submit their data profiles into a Data Bank who will offer incentives such as a reduction of insurance premiums to cash back rewards.

 

Everything from activity trackers, home automation, to vehicular automation data may be captured and aggregated.    The data collected can then be sliced and diced to provide macro and micro views of the information.    On the abstract, macro level the information may allow for demographic, statistical correlations, which may contribute to corporate strategy.

On a granular view, the data will provide “data banks” the opportunity to sift through data to perform analysis and correlations that lead to actionable information.

 

Is it secure?  Do you care if a hacker steals your weight loss information? May not be an issue if collected Purchase and Use Behavior Profiles aggregate into a Blockchain general ledger.  Data Curators and Aggregators work with SMEs to correlate the data into:

  • Canned, ‘intelligent’ reports targeted to specific subject matter, or across silos of data types
  • ‘Universes’ (i.e.  Business Objects) of data that may be ‘mined’ by consumer approved, ‘trusted’ third party companies, e.g. your insurance companies.
  • Actionable information based on AI subject matter rules engines

 

Consumers may have the option of sharing their personal data with specific companies by proxy, through a ‘data bank’ granular to the data point collected.  Sharing of Purchase and User Behavior Profiles:

  1. may lower [or raise] your insurance premiums
  2. provide discounts on preventive health care products and services, e.g. vitamins to yoga classes
  3. Targeted, affordable,  medicine that may redirect the choice of the doctor to an alternate.  The MD would be contacted to validate the alternate.

The curriated data collected may be harnessed by thousands of affinity groups to offer very discrete products and services.  Purchase and User Behavior Profiles,  correlated information stretches beyond any consumer relationship experienced today.

 

At some point, health insurance companies may require you to wear a tracker to increase or slash premiums.  Auto Insurance companies may offer discounts for access to car smart data to make sure suggested maintenance guidelines for service are met.

You may approve your “data bank” to give access to specific soliciting government agencies or private research firms looking to analyze data for their studies. You may qualify based on the demographic, abstracted data points collected for incentives provided may be tax credits, or paying studies.

 

Purchase and User Behavior Profiles:  Adoption and Affordability

If ‘Data Banks’ are able to collect Internet of Things (IoT) enabled, are cost inhibiting.  here are a few ways to increase their adoption:

  1.  [US] tax coupons to enable the buyer, at the time of purchase, to save money.  For example, a 100 USD discount applied at the time of purchase of an Activity Tracker, with the stipulation that you may agree,  at some point, to participate in a study.
  2. Government subsidies: the cost of aggregating and archiving Purchase and Behavioral profiles through annual tax deductions.  Today, tax incentives may allow you to purchase an IoT device if the cost is an itemized medical tax deduction, such as an Activity Tracker that monitors your heart rate, if your medical condition requires it.
  3. Auto, Life, Homeowners, and Health policyholders may qualify for additional insurance deductions
  4. Affinity branded IoT devices, such as American Lung Association may sell a logo branded Activity Tracker.  People may sponsor the owner of the tracking pedometer to raise funds for the cause.

The World Bank has a repository of data, World DataBank, which seems to store a large depth of information:

World Bank Open Data: free and open access to data about development in countries around the globe.”

Here is the article that inspired me to write this article:

http://www.marketwatch.com/story/you-might-be-wearing-a-health-tracker-at-work-one-day-2015-03-11

Privacy and Data Protection Creates Data Markets

Initiatives such as General Data Protection Regulation (GDPR) and other privacy initiatives which seek to constrict access to your data to you as the “owner”, as a byproduct, create opportunities for you to sell your data.  

Blockchain: Purchase, and User Behavior Profiles

As your “vault”, “Data Banks” will collect and maintain your two primary datasets:

  1. As a consumer of goods and services, a Purchase Profile is established and evolves over time.  Online purchases are automatically collected, curated, appended with metadata, and stored in a data vault [Blockchain].  “Offline” purchases at some point, may become a hybrid [on/off] line purchase, with advances in traditional monetary exchanges, and would follow the online transaction model.
  2. User Behavior (UB)  profiles, both on and offline will be collected and stored for analytical purposes.  A user behavior “session” is a use case of activity where YOU are the prime actor.  Each session would create a single UB transaction and are also stored in  a “Data Vault”.   UB use cases may not lead to any purchases.

These datasets wholly owned by the consumer, are safely stored, propagated, and immutable with a solution such as with a Blockchain general ledger.