The best place to start if we’re trying to improve the quality of our decisions is to look at how organizations make decisions.
When it comes to decisions, organizations default to gathering data and rarely analyzing decisions.
People aren’t taught to make decisions, they are taught coding, project management
Countdown approach
Data Informed Design - Good Tech Test - May 2018Courtney Clark
When it comes to design, everyone has an opinion! However, during reviews and discussions it’s those with more than an opinion that fair the best. Successful design solutions require a deep understanding of audiences, clear strategy, and good ole data.
In this session you’ll learn:
- Common data sources for design
- How to build a data-informed approach (not data-driven)
- What data-informed design looks like in the wild (aka case studies).
Whether you’re trying to prove a point, make an improvement, or discover something new, data-informed design moves your team from gut-feelings to fact-based decisions.
Business Growth and Enhancing Consumer Experience Through Online Payment Rashed Moslem
E Commerce is the next big thing in Bangladesh. I have prepared this presentation with industry data and my experience in digital industry. I tried to show how online payment can enhance consumer experience in the long run and how consumer behavior is changing over the time.
Data Informed Design - Good Tech Test - May 2018Courtney Clark
When it comes to design, everyone has an opinion! However, during reviews and discussions it’s those with more than an opinion that fair the best. Successful design solutions require a deep understanding of audiences, clear strategy, and good ole data.
In this session you’ll learn:
- Common data sources for design
- How to build a data-informed approach (not data-driven)
- What data-informed design looks like in the wild (aka case studies).
Whether you’re trying to prove a point, make an improvement, or discover something new, data-informed design moves your team from gut-feelings to fact-based decisions.
Business Growth and Enhancing Consumer Experience Through Online Payment Rashed Moslem
E Commerce is the next big thing in Bangladesh. I have prepared this presentation with industry data and my experience in digital industry. I tried to show how online payment can enhance consumer experience in the long run and how consumer behavior is changing over the time.
Warren Buffet would often think of companies as castles with a competitive moat protecting the business. Products or companies that figure out how to build and leverage differentiated data assets will be best positioned to win their respective markets. This talk describes the properties of a good data moat, why it matters, and how to go about building them within your organization.
Tips and Tricks to be an Effective Data ScientistLisa Cohen
Data Science is an evolving field, that requires a diverse skill set. From Analytical Techniques to Career Advice, this talk is full of practical tips that you can apply immediately to your job.
Propose a Human Resource Management strategy and specific organiza.docxbriancrawford30935
Propose a Human Resource Management strategy and specific organizational behaviors that are best suited for global business organizations.
The due diligence analyses on the three countries chosen – Canada, South Africa and China - will wrap up in this assignment with the exploration of management decision making processes. For each of the countries, you will discuss:
· the benefits bringing the diversity of the workforce will have for your company.
· compare and contrast the various aspects of U.S. human resource management against those of each country, Cananda, South Africa and China.
· examine what motivates the local workforce and the style of leadership which is prevalent in each of the countries - contrast those against what our U.S. company would utilize.
A minimum of two pages per country is required and you will follow APA (6th edition) formatting (no abstract is required for this milestone) with title and reference pages, indented paragraphs and a minimum of four APA formatted references and associated in-text citations.
GO to TED.com; search for and watch the TED talk by Roselinde Torres, What it takes to be a great leader.
Discussion 2
Data Management
After studying this week’s assigned readings, discussion the following:
1. What are the business costs or risks of poof data quality? Support your discussion with at least 3 references.
2. What is data mining? Support your discussion with at least 3 references.
3. What is text mining? Support your discussion with at least 3 references.
Please use APA throughout.
Post your initial response no later than Friday of week 3. Please note that initial post not completed on the due date will receive zero grade. See class syllabus for late assignment policies. Review posting/discussion requirements.
Read and respond to at two (2) of your classmates no later than the last day of week 3. In your response to your classmates, consider comparing your articles to those of your classmates. Below are additional suggestions on how to respond to your classmates’ discussions:
· Ask a probing question, substantiated with additional background information, evidence or research.
· Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
· Offer and support an alternative perspective using readings from the classroom or from your own research.
· Validate an idea with your own experience and additional research.
· Make a suggestion based on additional evidence drawn from readings or after synthesizing multiple postings.
· Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.
1) Respond to the below discussion with 150 words
Last 45 mins ago
1. What are the business costs or risks of poor data quality?
The individuals benefits of the business might make decided at the individuals majority of the data gathered besides poor info.
Foundational Strategies for Trust in Big Data Part 2: Understanding Your DataPrecisely
Teams working on new initiatives whether for customer engagement, advanced analytics, or regulatory and compliance requirements need a broad range of data sources for the highest quality and most trusted results. Yet the sheer volume of data delivered coupled with the range of data sources including those from external 3rd parties increasingly precludes trust, confidence, and even understanding of the data and how or whether it can be used to make effective data-driven business decisions.
The second part of our webcast series on Foundation Strategies for Trust in Big Data provides insight into how Trillium Discovery for Big Data with its natively distributed execution for data profiling supports a foundation of data quality by enabling business analysts to gain rapid insight into data delivered to the data lake without technical expertise.
Frank Bien, CEO of Looker - along with Amazon, Google and other data disrupters - discuss how innovators are deeply integrating analytics into every aspect of their businesses, from mobile to warehouse to cloud.
Frank shares Looker’s vision for the future of business intelligence and data analytics and reveal pivotal product and partnership updates.
Frank Bien, CEO of Looker - along with Amazon, Google and other data disrupters - discuss how innovators are deeply integrating analytics into every aspect of their businesses, from mobile to warehouse to cloud.
Frank shares Looker’s vision for the future of business intelligence and data analytics and reveal pivotal product and partnership updates.
RDAP13 Elizabeth Moss: The impact of data reuseASIS&T
Kathleen Fear, ICPSR, University of Michigan
“The impact of data reuse: a pilot study of 5 measures”
Panel: Data citation and altmetrics
Research Data Access & Preservation Summit 2013
Baltimore, MD April 4, 2013 #rdap13
Cut Through the Web Analytics Fog: Using GA Data Grabber to Act on Google Ana...Brian Alpert
A common chorus from museum professionals is how challenging it is to make data-driven decisions with which to improve their programs. Popular tools such as Google Analytics are intuitive and seemingly easy-to-use, yet when the time comes to use data to measure a program's stated goals, too often the main question surrounding the data is "So what?" This workshop will focus on bringing clarity to this challenge. Presented at MCN2012, on 11/7/12.
Humans, AI and Decisions Making - 3 - What are the editorial questions AI can...phillbjones
John Sack of Highwire press explores to what extent machines can participate in the editorial process of a scholarly journal. Including some interesting information about Highwire's collaboration with meta
SciVal offers quick, easy access to the research performance of 8,500 research institutions and 220 nations worldwide. A ready-to-use solution with unparalleled power and flexibility, SciVal enables you to visualize research performance, benchmark relative to peers, develop collaborative partnerships and analyze research trends.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Warren Buffet would often think of companies as castles with a competitive moat protecting the business. Products or companies that figure out how to build and leverage differentiated data assets will be best positioned to win their respective markets. This talk describes the properties of a good data moat, why it matters, and how to go about building them within your organization.
Tips and Tricks to be an Effective Data ScientistLisa Cohen
Data Science is an evolving field, that requires a diverse skill set. From Analytical Techniques to Career Advice, this talk is full of practical tips that you can apply immediately to your job.
Propose a Human Resource Management strategy and specific organiza.docxbriancrawford30935
Propose a Human Resource Management strategy and specific organizational behaviors that are best suited for global business organizations.
The due diligence analyses on the three countries chosen – Canada, South Africa and China - will wrap up in this assignment with the exploration of management decision making processes. For each of the countries, you will discuss:
· the benefits bringing the diversity of the workforce will have for your company.
· compare and contrast the various aspects of U.S. human resource management against those of each country, Cananda, South Africa and China.
· examine what motivates the local workforce and the style of leadership which is prevalent in each of the countries - contrast those against what our U.S. company would utilize.
A minimum of two pages per country is required and you will follow APA (6th edition) formatting (no abstract is required for this milestone) with title and reference pages, indented paragraphs and a minimum of four APA formatted references and associated in-text citations.
GO to TED.com; search for and watch the TED talk by Roselinde Torres, What it takes to be a great leader.
Discussion 2
Data Management
After studying this week’s assigned readings, discussion the following:
1. What are the business costs or risks of poof data quality? Support your discussion with at least 3 references.
2. What is data mining? Support your discussion with at least 3 references.
3. What is text mining? Support your discussion with at least 3 references.
Please use APA throughout.
Post your initial response no later than Friday of week 3. Please note that initial post not completed on the due date will receive zero grade. See class syllabus for late assignment policies. Review posting/discussion requirements.
Read and respond to at two (2) of your classmates no later than the last day of week 3. In your response to your classmates, consider comparing your articles to those of your classmates. Below are additional suggestions on how to respond to your classmates’ discussions:
· Ask a probing question, substantiated with additional background information, evidence or research.
· Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
· Offer and support an alternative perspective using readings from the classroom or from your own research.
· Validate an idea with your own experience and additional research.
· Make a suggestion based on additional evidence drawn from readings or after synthesizing multiple postings.
· Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.
1) Respond to the below discussion with 150 words
Last 45 mins ago
1. What are the business costs or risks of poor data quality?
The individuals benefits of the business might make decided at the individuals majority of the data gathered besides poor info.
Foundational Strategies for Trust in Big Data Part 2: Understanding Your DataPrecisely
Teams working on new initiatives whether for customer engagement, advanced analytics, or regulatory and compliance requirements need a broad range of data sources for the highest quality and most trusted results. Yet the sheer volume of data delivered coupled with the range of data sources including those from external 3rd parties increasingly precludes trust, confidence, and even understanding of the data and how or whether it can be used to make effective data-driven business decisions.
The second part of our webcast series on Foundation Strategies for Trust in Big Data provides insight into how Trillium Discovery for Big Data with its natively distributed execution for data profiling supports a foundation of data quality by enabling business analysts to gain rapid insight into data delivered to the data lake without technical expertise.
Frank Bien, CEO of Looker - along with Amazon, Google and other data disrupters - discuss how innovators are deeply integrating analytics into every aspect of their businesses, from mobile to warehouse to cloud.
Frank shares Looker’s vision for the future of business intelligence and data analytics and reveal pivotal product and partnership updates.
Frank Bien, CEO of Looker - along with Amazon, Google and other data disrupters - discuss how innovators are deeply integrating analytics into every aspect of their businesses, from mobile to warehouse to cloud.
Frank shares Looker’s vision for the future of business intelligence and data analytics and reveal pivotal product and partnership updates.
RDAP13 Elizabeth Moss: The impact of data reuseASIS&T
Kathleen Fear, ICPSR, University of Michigan
“The impact of data reuse: a pilot study of 5 measures”
Panel: Data citation and altmetrics
Research Data Access & Preservation Summit 2013
Baltimore, MD April 4, 2013 #rdap13
Cut Through the Web Analytics Fog: Using GA Data Grabber to Act on Google Ana...Brian Alpert
A common chorus from museum professionals is how challenging it is to make data-driven decisions with which to improve their programs. Popular tools such as Google Analytics are intuitive and seemingly easy-to-use, yet when the time comes to use data to measure a program's stated goals, too often the main question surrounding the data is "So what?" This workshop will focus on bringing clarity to this challenge. Presented at MCN2012, on 11/7/12.
Humans, AI and Decisions Making - 3 - What are the editorial questions AI can...phillbjones
John Sack of Highwire press explores to what extent machines can participate in the editorial process of a scholarly journal. Including some interesting information about Highwire's collaboration with meta
SciVal offers quick, easy access to the research performance of 8,500 research institutions and 220 nations worldwide. A ready-to-use solution with unparalleled power and flexibility, SciVal enables you to visualize research performance, benchmark relative to peers, develop collaborative partnerships and analyze research trends.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
4. www.wardpeter.com
About Me
{
background : “Founder- former CTO ",
employee : “SoHo Dragon",
skill : “SharePoint, O365",
books : “Co author of 4 SharePoint books”
writing : “Leadership in a zoom economy with Microsoft Teams”
Co organizer : “SharePoint Saturday New York, Meetup”
1St Sharepoint : Version SharePoint Portal 2003
hobbies : “Yoga, cooking vegetarian food",
}
5. NEW TEAMS BOOK
Leadership in a Zoom Economy with Microsoft Teams: Applying Leadership to a Remote Workforce
You are the best-looking audience I’ve seen. In fact you are better looking than the people in todays keynote
The best place to start if we’re trying to improve the quality of our decisions is to look at how organizations make decisions.
. When it comes to decisions, organizations default to gathering data and rarely analyzing decisions.
People aren’t taught to make decisions, they are taught coding, project management
Countdown approach
All non technical
Odds are three things went into that decision:
It probably relied on the insights of a few key executives;
(2) it involved some sort of fact gathering and analysis; and
(3) it was likely enveloped in some sort of decision process—whether formal or informal—that translated the analysis into a decision.
Now how would you rate the quality of your organization’s strategic decisions?
If you’re like most workers, the answer wouldn’t be positive:
This session is asking: What is really going on? THIS DOESN’T MAKE SENSE
Most business decisions were not made on “gut calls” but rather rigorous analysis.
And yet they were poor decisions. In short, most people did the all the legwork we think we’re supposed to do: they delivered large quantities of detailed analysis.
Yet this wasn’t enough. “research indicates that, contrary to what one might assume, good analysis in the hands of managers who have good judgment won’t naturally yield good decisions.”
People aren’t taught how to make decisions.
Projections are put together by people who are interested in a particular outcome, have a subconscious bias, and their apparent precision makes it fallacious.
Sales people
As an executive, I need accuracy and truth.
The young and the old lady.
To make better decisions, we can sort of reduce errors or have better insight or preferably both.
And yet, these often seem in conflict with one another. I thought a good place to start this would be, what sparks insight and what prevents us from putting our insights into use? Is it because they often contradict the beliefs we hold?
Are they giving you all the data
To be a good manager, you want things to run smoothly. And insights are not ways of running smoothly. Insights are disorganizing and disruptive. And so, that’s a major reason that organizations, without even intending to, block the insights that come their way. Give them reports to what they control
More data doesn’t mean better outcomes
But insights are disorganizing, as you point out. Insights make you change the way you think, and make you change all kinds of things. And they may not be right. And so, most organizations actually inhibit insights.
Insights- Leaders
Middle Managers – Operational Reports
Is that because the organizations are mostly focused on the error-reducing side versus the gaining insight side, and that’s the tension between these things? They don’t like variants. They don’t like things that are outside of the norm.
Emotional and logistic lenses
How do you valid the data
Content is important
Who’s correct
The BI developer should ask- What decision will you be making from this report
Are we experimenting? Or are we set on the process
A second type of insight is contradiction insight, where something happens that doesn’t make sense.
And there you do have to change what you believe or wonder what’s going on.
And the example I use there is a story I heard from a police officer. He was driving around with a partner who was in his first year, and they were stuck in traffic. There’s a red light. And the partner, this young guy looks at the car ahead, which is a new BMW.
And he sees the driver take a deep drag on a cigarette and then flick the ashes.
And he says, “Who flicks the ashes in a brand new BMW? That doesn’t make sense. Something is off here.”
So they light them up, and pull the car over. Sure enough, it was a stolen car. So that’s the second type of insight, which is a contradiction insight, where something happens that you didn’t expect. Now, this didn’t force anybody to revise their mental model of their thinking. It just allowed them to investigate further.
a misconception resulting from incorrect information.
So in terms of insight, in terms of changing our beliefs, that’s the secret sauce for this kind of pathway, where even practically for any of the pathways, is to become curious about things that don’t make sense.
People with lots of experience. And I found that experience is essential for coming up with insights.
However, people with experience have lots of scar tissue, from things that got tried before and failed. . People with lots of experience. And I found that experience is essential for coming up with insights.
I’ll ask them, “Tell me the last mistake you made. Let’s talk about that.”
Journyman are not experts
Understand experience - 20 years is not 20 years of learning
Experience, and they probably worked in a job very similar to the one that you’re working in now. The problem is, their experience in that role was 20 years ago or 15 years ago. And I would imagine that the environment has changed a lot, whereas the experience of your manager or your team leader, or whatever, might be more recent, and they would have a more accurate view to what the lay of the land is right now.
Executives are the best at this
Look at historic data. How do we evaluate someone’s ability to make decisions?
What got you to that decision
Who are you?
New employees wanting to change everything
Did the person get lucky…… is this the only piece of evidence we have? So you can’t just look at the outcome, but you have to look at what the person was thinking about when they made the decision
I think the idea of a decision journal is a great idea. And I hadn’t heard of that before.
I would like to know when the employee is making a decision, what is the decision, what are the goals that the employee wants to achieve.
The primary goal, but there may be other goals that the employee is aware of. What are the prime pieces of information the employee is using to make the decision? Who are the other people or teams that are going to be affected by this decision? Those are the things that I’d like to examine.
I found that 80% of my cleanup was made from 20% of the decisions
we should discourage people from coming up with immediate reactions, but that’s ridiculous, because that’s not the way we think, and it would cripple us.
When do I need to make this decision? Do I have the freedom.
So instead, you want us to come up with a quick reaction, but if we’re wrong, there’s going to be an anomaly, and we want to be able to revisit it. That’s the way we break out of fixation, is we notice the anomalies. The way we get stuck in fixation and make fixation errors is we explain away the anomalies, hold on to the original wrong impression until it’s far too late.
Cognitive flexibility theory is the notion of trying to help people achieve expertise by preventing them from locking into routines and standard ways of doing things so that they can become more naturally adaptive.
Instead of doing a postmortem for projects that fail after they failed, let’s move it to the beginning.” And that’s why it’s called a pre-mortem. And the way it works is if we’re on a team, we take everybody on the team, we’re all sitting around the table. And usually we do it at a kickoff meeting, Post Mortem. Helps everyone but the patient.
What we find is it surfaces ideas and flaws that people hadn’t considered.
But it also creates a culture of candor in the team, where people are starting to get used to expressing problems rather than covering them up.
And it creates a sense of trust that I can say something and I’m not going to get criticized for it.
Often at the end of a meeting, somebody will say, “All right, we’re just about done with the meeting. Does anybody see any problems?” Nobody wants to identify a problem. We’ve just spent the last hour and a half discussing the plan.
Nobody wants to admit that there’s a problem. People aren’t even thinking about problems. They’re all in goal mode. Let’s get started. They’re impatient to start. And there could be consequences of exposing problems. With a pre-mortem, we reversed that dynamic. The way you show your smart in a pre-mortem is the quality of the items that you generate.
So, there’s no general rule for how a team should make a decision. It’s going to depend on the situation and the context.
There was a movie with Matt Damon a number of years ago called The Martian. And Matt Damon is part of a team that went to Mars. And something happened and they needed to depart, and they gathered everybody together, but they couldn’t find Matt Damon.
I don’t like the idea of consensus decisions. And I don’t like the idea of a consensus decision in this kind of dangerous environment. Because as the people in the spaceship went around, there was enormous pressure on everybody to go along with the consensus, which was, “We should go back and rescue him.”
And it was public. And they went back and they risked all of their lives in order to save him.
US army – We defend democracy, not practice it.
When you go to a meeting to make a decision, have everybody in the room write out the problem on a piece of paper that they think they’re solving with this decision, and then compare how different and how much variance there is in those problem statements.
Do we have the right insight into the problem?
Have we defined the problem?” And this is where if you have a sole decision maker instead of a group, you can acknowledge that the responsibility of that decision maker may be to listen to other people’s definitions of the problem.
I love the idea of the zone of indifference.
The way the phenomenon works is if I’ve got two choices, a terrible option, and a wonderful option, quick, which one do you pick? Okay, that’s not a hard decision. These are the hardest decisions people ever wrestle with. And the paradox is if the advantages and disadvantages of the two options are almost perfectly balanced, it doesn’t matter which one we pick.