Slack & Flickr Founder Stewart Butterfield Interviews with NPR

Excellent, Well Told “Rags to Riches” Interview with the Founder of Slack, Stewart Butterfield

In the early 2000s, Stewart Butterfield tried to build a weird, massively multiplayer online game, but the venture failed.

Instead, he and his co-founders used the technology they had developed to create the photo-sharing site Flickr.

After Flickr was acquired by Yahoo in 2005, Butterfield went back to the online game idea, only to fail again.

But the office messaging platform Slack rose from the ashes of that second failure — a company which, today, is valued at over $5 billion.

Click through to the Audio Recording of the Interview.

Source: Slack & Flickr: Stewart Butterfield : NPR

Continuing Certification Requirements for Project Management Professional (PMP)

The years seem to have flown by, and it’s that time again to complete my Continuing Certification Requirements for my PMP cert.

I randomly searched the web for PMP courses, then found myself back at PMI.org “Searching Activities”.  Seems like the easiest way to lookup activities because they define the activities, and the correlated list of Professional Development Units, categorized by:

  • Technical
  • Leadership
  • Strategic & Business

Based on the activities I’ve already completed, my majority of work has been accomplished in the Technical category.  I need to focus on attaining Leadership and Strategic & Business categories.

PMP 2019 Continuing Certification Requirements
PMP 2019 Continuing Certification Requirements

Here are a few activities I thought were interesting.  Appreciate your feedback on these courses, or others relating to Leadership or Strategic & Business.

Agile Team Challenges

This online course is designed to help Agile practitioners decipher and solve the problems that arise regularly in their work. The course consists of 20 short case studies that test the student’s understanding of Agile practices and provide guidance for resolving common problems

Technical: 2.00 Leadership: 2.00

Integrating Agile and Waterfall Practices

This online course is designed to help Agile proponents recognize and resolve many of the common integration issues that emerge when these two methodologies are combined. The course consists of 20 short case studies that simulate the communication and interchanges that can occur as Agile and Waterfall practitioners work to resolve differences in the ways that they see and execute tasks.

Technical: 1.00 Leadership: 1.00  Strategic & Business: 1.00

Agile for Business Analysts – How a Business Analyst Survives in an Agile Business World

The agile philosophy in software development and in management is one of flexibility and responsiveness, increased communication and just in time decision making, and the removal of barriers of bureaucracy between the business problem and the solution. The agile approach appears to be in direct opposition to intermediaries and interpreters. Extended analytical processes are replaced by short delivery cycles. Business analysts, acting as intermediaries between those with the problem and those with the solution, providing analysis of the business processes and defining requirements that delineate the solution, may find their role evaporating in the agile sunlight. Is the role of business analyst being marginalized by agile development? What does the business analyst do in the new agile environment?

Technical: 5.50 Leadership: 4.50  Strategic & Business: 2.00

Assessing, Managing, and Mitigating Project Risk

Risk management is a key function in project management. Project managers should be able to apply a variety of risk-management tools in their work, including performing risk identification, quantification, response, monitoring, and control.

Technical: 3.00 Leadership: 3.00  Strategic & Business: 4.00

Managing Conflict on Project Teams

As a project leader you need to be able to distinguish between when conflict is healthy and when it’s damaging to relationships and productivity. In this course, authored by Cornell Instructor Robert Newman, you’ll learn to identify various causes and sources of conflict and learn to foster healthy disagreement within a project team.

Leadership: 5.00  Strategic & Business: 1.00

Agile Risk Management

Software componentization has made software more unpredictable because unforeseen conditions can cause components to interact in ways we hadn’t imagined. Greater complexity, increased user expectations, and our desire to use agile with ever increasing velocity require that we actively manage uncertainties and risks. Classic risk management identifies risks and prioritizes them to determine impact to the project, but how does that differ in an agile project? Agile is designed to handle uncertainty in requirements as new features are requested and priorities shift. What about the uncertainties outside of requirements changes? Understanding those risks even before the project gets started—and those that can possibly derail the project after delivery—is critical. Phil Lew and Moss Drake provide insight into the uncertainties and risks involved in agile software projects and supplements classic risk management approaches with how and when to apply within an agile process.

Technical: 3.25

Popular Tweets from March, April, and May 2018

Tweet Activity Analytics

Leveraging Twitter’s Analytics, I’ve extracted my top Tweets from the last 91 day period.   During that time there were 42.2K impressions earned.  Looks like I took a slump on my statistics.

Summary:

  • 38 Link Clicks
  • 6 Retweets
  • 24 Likes
  • 14 Replies
March, April, May 2018 Tweets
March, April, May 2018 Tweets

People Turn Toward “Data Banks” to Commoditize on their 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 for a 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 and consumer rule transparency may be provided.

 

 “Data Banks” may be required to report to their customers who agreed to sell their data examples of specific rows of the data, which was sold on a “Data Market”.

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 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 allowed to collect Internet of Things (IoT) device profile and the devices themselves are cost prohibitive.  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.

Not all Purchase and User Behavior profiles are created equal.  Eg. One person’s profile may show a monthly spend higher than another.  The consumer who purchases more may be entitled to more benefits.

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

Man Trains Dog. Dog Trains AI Model. Cats Rule the World.

Researchers Teach AI to Think like a Dog

Source: Researchers teach AI to think like a dog and find out what they know about the world – The Verge

Animals could provide a new source of training data for AI systems.

To train AI to think like a dog, the researchers first needed data. They collected this in the form of videos and motion information captured from a single dog, a Malamute named Kelp. A total of 380 short videos were taken from a GoPro camera mounted to the dog’s head, along with movement data from sensors on its legs and body.

They captured a dog going about its daily life — walking, playing fetch, and going to the park.

Researchers analyzed Kelp’s behavior using deep learning, an AI technique that can be used to sift patterns from data, matching the motion data of Kelp’s limbs and the visual data from the GoPro with various doggy activities.

The resulting neural network trained on this information could predict what a dog would do in certain situations. If it saw someone throwing a ball, for example, it would know that the reaction of a dog would be to turn and chase it.

The predictive capacity of their AI system was very accurate, but only in short bursts. In other words, if the video shows a set of stairs, then you can guess the dog is going to climb them. But beyond that, life is simply too varied to predict. 

 

Dogs “clearly demonstrate visual intelligence, recognizing food, obstacles, other humans, and animals,” so does a neural network trained to act like a dog show the same cleverness?

It turns out yes.

Researchers applied two tests to the neural network, asking it to identify different scenes (e.g., indoors, outdoors, on stairs, on a balcony) and “walkable surfaces” (which are exactly what they sound like: places can walk). In both cases, the neural network was able to complete these tasks with decent accuracy using just the basic data it had of a dog’s movements and whereabouts.

Dog AI Model Training
Dog AI Model Training

 

Blended Data Warehouse SW/HW Solutions Phased Into the Cloud

Relational Database Solutions “In a Box”

Several of the relational database software vendors, such as IBM, Oracle, and Teradata have developed proprietary data warehouse software to be tightly coupled with server hardware to maximize performance.  These solutions have been developed and refined as “on-prem” solutions for many years.

We’ve seen the rise of “Database (DW)  as a Service” from companies like Amazon, who sell Redshift services.

Amazon Redshift is a fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools.  It allows you to run complex analytic queries against petabytes of structured data, using sophisticated query optimization, columnar storage on high-performance local disks, and massively parallel query execution. Most results come back in seconds.

RDB Complex Software/Hardware Maintenance

In recent times, the traditional relational database software vendors shifted gears to become service providers offering maximum performance from a solution hosted by them, the vendor, in the Cloud.    On the positive side, the added complexity of configuring and tuning a blended software/hardware data warehouse has been shifted from the client’s team resources such as Database Administrators (DBAs), Network Administrators,  Unix/Windows Server Admins,… to the database software service provider.  The complexity of tuning for scalability, and other maintenance challenges shifts to the software vendor’s expertise, if that’s the abstraction you select.  There is some ambiguity in the delineation of responsibilities with the RDBMS vendor’s cloud offerings.

Total Cost of Ownership

Quantifying the total cost of ownership of a solution may be a bit tricky, especially if you’re trying to quantify the RDBMS hybrid software/hardware “on-prem” solution versus the same or similar capabilities brought to the client via “Database (DW) as a Service”.

“On-Prem”, RDB Client Hosted Solution

Several factors need to be considered when selecting ANY software and/or Hardware to be hosted at the client site.

  • Infrastructure “when in Rome”
    • Organizations have a quantifiable cost related to hosting physical or virtual servers in the client’s data center and may be boiled down to a number that may include things like HVAC, or new rack space.
    • Resources used to maintain/monitor DC usage, there may be an abstracted/blended figure.
  • Database Administrators maintain and monitor RDB solutions.
    • Activities may range from RDB patches/upgrades to resizing/scaling the DB storage “containers”.
    • Application Database Admins/Developers may be required to maintain the data warehouse architecture, such as new requirements, e.g. creating aggregate tables for BI analysis.
  • Network Administrators
    • Firewalls, VPN
    • Port Scanning
  • Windows/Unix Server Administrators
    • Antivirus
    • OS Patches

Trying to correlate these costs in some type of “Apples to Apples” comparison to the “Data Warehouse as a Service” may require accountants and technical folks to do extensive financial modeling to make the comparison.   Vendors, such as Oracle, offer fully managed services to the opposite end of the spectrum, the “Bare Metal”, essentially the “Infra as a Service.”  The Oracle Exadata solution can be a significant investment depending on the investment in redundancy and scalability leveraging Oracle Real Application Clusters (RAC). 

Support and Staffing Models for DW Cloud Vendors

In order for the traditional RDB software vendors to accommodate a “Data Warehouse as a Service” model, they may need to significantly increase staff for a variety of technical disciplines, as outlined above with the Client “On-Prem” model.  A significant ramp-up of staff and the organizational challenges of developing and implementing a support model based on a variety of factors may have relational database vendors ask: Should they leverage a top tier consulting agency such as Accenture, or Deloitte to define, implement, and refine a managed service?  It’s certainly a tall order to go from a software vendor to offering large scale services.  With corporate footprints globally and positive track records implementing managed services of all types, it’s an attractive proposition for both the RDB vendor and the consulting agency who wins the bid.  Looking at the DW Service billing models don’t seem sensical on some level.  Any consulting agency who implements a DW managed service would be responsible to ensure ROI both for the RDS vendor and their clients.  It may be opaque to the end client leveraging the Data Warehouse as a Service, but certainly, the quality of service provided should be nothing less than if implemented by the RDB vendor itself.  If the end game for the RDB vendor is for the consulting agency to implement, and mature the service then at some point bring the service in-house, it could help to keep costs down while maturing the managed service.

Oracle Exadata

Here are URLs for reference to understand the capabilities that are realized through Oracle’s managed services.

https://cloud.oracle.com/en_US/database

https://cloud.oracle.com/en_US/database/exadata/features

https://www.oracle.com/engineered-systems/exadata/index.html

Teradata

https://www.teradata.com/products-and-services/intellicloud

https://www.teradata.com/products-and-services/cloud-overview

Teradata
Teradata

DB2

https://www.ibm.com/cloud/db2-warehouse-on-cloud

IBM Mainframe
IBM Mainframe

Note: The opinions shared here are my own.

Bose AR, Audio Augmented Reality – Use Cases

I’ve been enamored with Bose products for well over a decade. However,  we’ve seen quality brands enter the hi-fidelity audio market over that time.  Beyond quality design in their classic audio products, can Bose Augmented Reality (Bose AR) be the market differentiator?

Bose: Using a Bose-AR-equipped wearable, a smartphone, and an app-enabled with Bose AR, the new platform lets you hear what you see.

It sounds like Bose may come up with an initial design, sunglasses, but turn to 3rd party hardware manufacturers of all sorts to integrate Bose AR into other wearable products.

Bose Augmented Reality isn’t just about audio. The devices will use sensors to track head motions for gesture controls and work with GPS from a paired smartphone to track location.  The company also aspires to combine visual information with the Bose AR platform.

Bose AR Use Cases

  • Bose Augmented Reality device reenact historical events or speeches from landmarks and statues as you visit them.
  • The Bose and NFL partnership could be leveraged to get these AR units into the football player’s helmets.  Audio queues from the on-field lead, quarterback, and dynamically replayed/relayed at the appropriate time of required action by the receiver.
  • Audio directions to your gate when your GPS detects that you’ve arrived at the airport, or any other destination from your calendar.  Audio queues would be richer the more inclusive you are to the access to Calendars, To Do lists, etc.
  • Combine visual information with the Bose AR platform, too, so you could hear a translation of a sign you’re looking at.
  • Hear the history of a painting in a museum.

Time until it’s in consumer’s hands?  TBD.  Bose objective is to have the developer kit, including a pair of glasses, available later this year.

When I was on vacation in Athens, Greece, I created a post which had Greek actors running tours in their ancient, native garb.  The Bose AR could be a complementary offering to the tour, which includes live, greek local actors portraying out scenes in ancient ruins.  Record the scenes, and interact with them while walking through the Greek ruins in your Bose AR (Augmented Reality) glasses.

Greece, Prosperity, and Taxes: The World Will Come See You in AR

Please take a moment to prioritize the use cases, or add your own.

Takeaway

I’m a cheerleader for Bose, among several others in this space, but I question a Bose AR headset that produces a high fidelity sound. Most of the use cases listed should be able to “get along OK” with an average quality sound.  Maybe high definition AR games with a high level of realism might benefit from the high-quality sound. However, their site reads like Bose is positioning themselves as a component to be integrated into other AR headsets, i.e. “Bose-AR-equipped wearable

Information Architecture: An Afterthought for Content Creation Solutions

Maximizing Digital Asset Reuse

Many applications that enable users to create their own content from word processing to graphics/image creation have typically relied upon 3rd party Content Management Solutions (CMS) / Digital Asset Management (DAM) platforms to collect metadata describing the assets upon ingestion into their platforms.  Many of these platforms have been “stood up” to support projects/teams either for collaboration on an existing project, or reuse of assets for “other” projects.  As a person constantly creating content, where do you “park” your digital resources for archiving and reuse?  Your local drive, cloud storage, or not archived?

Average “Jane” / “Joe” Digital Authors

If I were asked for all the content I’ve created around a particular topic or group of topics from all my collected/ingested digital assets, it may be a herculean search effort spanning multiple platforms.  As an independent creator of content, I may have digital assets ranging from Microsoft Word documents, Google Sheets spreadsheets, Twitter tweets,  Paint.Net (.pdn) Graphics, Blog Posts, etc.

Capturing Content from Microsoft Office Suite Products

Many of the MS Office content creation products such as Microsoft Word have minimal capacity to capture metadata, and if the ability exists, it’s subdued in the application.  MS Word, for example, if a user selects “Save As”, they will be able to add/insert “Authors”, and Tags.  In Microsoft Excel, latest version,  the author of the Workbook has the ability to add Properties, such as Tags, and Categories.  It’s not clear how this data is utilized outside the application, such as the tag data being searchable after uploaded/ingested by OneDrive?

Blog Posts: High Visibility into Categorization and Tagging

A “blogging platform”, such as WordPress, places the Category and Tagging selection fields right justified to the content being posted.  In this UI/UX, it forces a specific mentality to the creation, categorization, and tagging of content.  This blogging structure constantly reminds the author to identify the content so others may identify and consume the content.  Blog post content is created to be consumed by a wide audience of interested viewers based on those tags and categories selected.

Proactive Categorization and Tagging

Perpetuate content classification through drill-down navigation of a derived Information Architecture Taxonomy.  As a “light weight” example, in WordPress, the Tags field when editing a Post, a user starts typing in a few characters, an auto-complete dropdown list appears to the user to select one or more of these previously used tags.  Excellent starting point for other Content Creation Apps.

Users creating Blog Posts can define a Parent/Child hierarchy of categories, and the author may select one or more of relevant categories to be associated with the Post.

Artificial Intelligence (AI) Derived Tags

It wouldn’t be a post without mentioning AI.  Integrated into applications that enable user content creation could be a tool, at a minimum, automatically derives an “Index” of words, or tags.  The way in which this “intelligent index” is derived may be based upon:

  • # of times word occurrence
  • mention of words in a particular context
  • reference of the same word(s) or phrases in other content
    • defined by the same author, and/or across the platform.

This intelligently derived index of data should be made available to any platforms that ingest content from OneDrive, SharePoint, Google Docs, etc.  These DAMs ( or Intelligent Cloud Storage) can leverage this information for any searches across the platforms.

Easy to Retrieve the Desired Content, and Repurpose It

Many Content Creation applications heavily rely on “Recent Accessed Files” within the app.  If the Information Architecture/Taxonomy hierarchy were presented in the “File Open” section, and a user can drill down on select Categories/Subcategories (and/or tags), it might be easier to find the most desired content.

All Eyes on Content Curation: Creation to Archive
  • Content creation products should all focus on the collection of metadata at the time of their creation.
  • Using the Blog Posting methodology, the creation of content should be alongside the metadata tagging
  • Taxonomy (categories, and tags with hierarchy) searches from within the Content Creation applications, and from the Operating System level, the “Original” Digital Asset Management solution (DAM), e.g. MS Windows, Mac

 

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

Information Architecture (IA): the Classification of Information (Part 2)

Karl Smith has created this timeless post on Information Architecture, which is still relevant today. The below is an excerpt of his article I found relevant to the foundation of IA.


To Each His Own

Different groups of individuals have a very specific context of use when looking for content, the descriptions they use and understand to find it and their underlying purpose in doing so. In this case, they will each require a separate structure around an entity and may require their own version of the taxonomy.

Atomic Unit of Information

Define ‘What is the smallest component of viable (useful) information?’ and use that to model the information system. I have worked with several huge education providers and universities and the questions I ask is ‘What is a course?’;

  • A course has a title
  • A course has duration, with a start and an end
  • A course has a subject
  • A course has a level
  • A course has prerequisites
  • A course has an outcome, which leads to options
  • A course has a delivery mechanism

I also ask, ‘Who is a student?’, ‘Who is a tutor?’, ‘What is an outcome?’ even ‘What is a college?’, if a course has a regular location then this creates a second set of entities.

  • A location has an address, telephone number, email address
  • A location has facilities
  • A location has transportation links
  • A location has a community
  • A location has accommodation

And it goes on and on, this is Information Architecture 101.

Source: Information Architecture (IA) the classification of information Part 2 – Karl Smith

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