The document discusses challenges with hiring data scientists and suggests alternative approaches. It recommends empowering small cross-functional data-oriented teams explicitly tasked with delivering measurable business benefits. This builds internal data capabilities rather than just hiring expertise. It also stresses the importance of making data science a cultural value throughout the organization so that all employees understand basic principles and practices of data science.
Stop searching for that elusive data scientistAbhi Rana
Look beyond the charm of data scientist in the organisation and find easy, quick and low-cost solutions. Team collaboration and peer learning is one the best way for small firms.
When it comes to people analytics, there just aren’t sufficient data points that provide a large enough data sample to apply “Big Data” techniques. Small data can facilitate meaningful conversations between line managers and HR. Hence, the best way to jump-start your people analytics capability is to start with small data.
Stop searching for that elusive data scientistAbhi Rana
Look beyond the charm of data scientist in the organisation and find easy, quick and low-cost solutions. Team collaboration and peer learning is one the best way for small firms.
When it comes to people analytics, there just aren’t sufficient data points that provide a large enough data sample to apply “Big Data” techniques. Small data can facilitate meaningful conversations between line managers and HR. Hence, the best way to jump-start your people analytics capability is to start with small data.
Welcome to the Chief Analytics Officer Forum Europe
On 7th – 9th March 2016, over 80 Chief Analytics Officers and senior analytics leaders met in London for intimate, top-level discussions; dissecting the role of the CAO, exploring innovative case studies and addressing mutual cross-industry challenges. To learn more, visit http://www.caoforumeurope.com/
This event is organised by http://coriniumintelligence.com/
Grow Your Own - How to Create a Data Culture at Your OrganizationLuciano Pesci, PhD
80% of data projects fail. How can something so promising be failing so badly? While organizations are scrambling to stay competitive by hiring data-talent, they don't fully understand the types available, how to integrate them into existing workflows, what to expect from their efforts, and how to gauge success.
You can watch the accompanying Webinar here: https://youtu.be/MUv-tqMHbvs
Week2day2 communicating data for impactNishant Kumar
This presentation is based on an article “ Data is Worthless if You Don’t Communicate It ” by Thomas H. Davenport published under Harvard Business review in year 2013 .
The problem of hiring the data scientist and how difficult it sometimes is to hire the right data scientist and what steps a manager can take to overcome this
Which is the primary key which unlocks the value of the Big Data? In a world awash with data, I argue in this presentation that narratives play a crucial role in making sense of the information. I look at the role of narratives in the data-scarce paradigm and look at some familiar consulting narratives. I then examine the implications of such narratives and look at how these narratives would change in the emerging data-ubiquity paradigm
Webinar presented to Cognizant Analytics Audiences on Context, Narratives & Big Data Analytics. This presentation draws from my previous presentation made at a conference on Narratives & Big Data.
#MITXData "Leveraging Data and Analytics for Your Marketing Strategy" present...MITX
-Jesse Harriott, Ph.D., Chief Analytics Officer, Constant Contact
-Dave Krupinksi, Co-Founder & Chief Technology Officer, Care.com
You may remember the days before the Web, social media, mobile, and Big Data. Instinct was a prized business characteristic and it, rather than data, drove many corporate marketing decisions.Companies now say that they are "data-driven" and only make quantitative marketing decisions. But these same companies are also overwhelmed by the sheer volume of data at their disposal and how to best analyze it to shape critical marketing questions. The issue today is not the lack of data, but rather how to prioritize, access, and use data in real time so it has the greatest impact on your business.
During this opening keynote, two top analytic leaders from major brands, Constant Contact and Care.com, will share best practices and proven strategies for incorporating analytics into your marketing strategy. Join Jesse Harriott, Chief Analytics Officer at Constant Contact, and Dave Krupinski, Co-founder and Chief Technology Officer at Care.com, as they discuss strategies to leverage data and analytics tools to inform marketing decisions and realize substantial ROI.
Loras College 2014 Business Analytics Symposium | Gebhard Rainer: Building a ...Cartegraph
We are data rich and information poor--many companies have lived through the same challenges. We used to look at data in standard form and try to justify why things did not go the way they were planned and forecasted. We performed "autopsies on dead bodies but never brought them back to life, instead of finding a remedy for cure to deal with the future!"
Now we analyze data from multiple sources, establish patterns and cross references and then work on predictable models to allow Strategic Planning with a high degree of insight and proactive priority setting.
It's a mind shift and mind-set change that has taken a hold of the company and is pervasive down to the lowest level of planning. Constant change is what challenges us to continuously question our own models and improve in order to manage our business successfully.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Dashboards are Dumb Data - Why Smart Analytics Will Kill Your KPIsLuciano Pesci, PhD
Organizations of every size have access to data dashboard technology, yet none of the solutions have delivered on their hype and right now across the world executives and analysts are staring at a dashboard and thinking the same thing, ""so what?""
The failure of dashboards to deliver meaningful insights is inherent in their simplicity: they only show surface level information, and not the relationships between data points that really drive the fate of your organization.
But all is not lost! By combining the right mix of technology and human expertise in business strategy, research and data mining you can embrace the smart analytics movement, and start accessing insights that grow your company and your competitive position.
You can watch the accompanying webinar here: https://youtu.be/RdOcPxv9wLs
Welcome to the Chief Analytics Officer Forum Europe
On 7th – 9th March 2016, over 80 Chief Analytics Officers and senior analytics leaders met in London for intimate, top-level discussions; dissecting the role of the CAO, exploring innovative case studies and addressing mutual cross-industry challenges. To learn more, visit http://www.caoforumeurope.com/
This event is organised by http://coriniumintelligence.com/
Grow Your Own - How to Create a Data Culture at Your OrganizationLuciano Pesci, PhD
80% of data projects fail. How can something so promising be failing so badly? While organizations are scrambling to stay competitive by hiring data-talent, they don't fully understand the types available, how to integrate them into existing workflows, what to expect from their efforts, and how to gauge success.
You can watch the accompanying Webinar here: https://youtu.be/MUv-tqMHbvs
Week2day2 communicating data for impactNishant Kumar
This presentation is based on an article “ Data is Worthless if You Don’t Communicate It ” by Thomas H. Davenport published under Harvard Business review in year 2013 .
The problem of hiring the data scientist and how difficult it sometimes is to hire the right data scientist and what steps a manager can take to overcome this
Which is the primary key which unlocks the value of the Big Data? In a world awash with data, I argue in this presentation that narratives play a crucial role in making sense of the information. I look at the role of narratives in the data-scarce paradigm and look at some familiar consulting narratives. I then examine the implications of such narratives and look at how these narratives would change in the emerging data-ubiquity paradigm
Webinar presented to Cognizant Analytics Audiences on Context, Narratives & Big Data Analytics. This presentation draws from my previous presentation made at a conference on Narratives & Big Data.
#MITXData "Leveraging Data and Analytics for Your Marketing Strategy" present...MITX
-Jesse Harriott, Ph.D., Chief Analytics Officer, Constant Contact
-Dave Krupinksi, Co-Founder & Chief Technology Officer, Care.com
You may remember the days before the Web, social media, mobile, and Big Data. Instinct was a prized business characteristic and it, rather than data, drove many corporate marketing decisions.Companies now say that they are "data-driven" and only make quantitative marketing decisions. But these same companies are also overwhelmed by the sheer volume of data at their disposal and how to best analyze it to shape critical marketing questions. The issue today is not the lack of data, but rather how to prioritize, access, and use data in real time so it has the greatest impact on your business.
During this opening keynote, two top analytic leaders from major brands, Constant Contact and Care.com, will share best practices and proven strategies for incorporating analytics into your marketing strategy. Join Jesse Harriott, Chief Analytics Officer at Constant Contact, and Dave Krupinski, Co-founder and Chief Technology Officer at Care.com, as they discuss strategies to leverage data and analytics tools to inform marketing decisions and realize substantial ROI.
Loras College 2014 Business Analytics Symposium | Gebhard Rainer: Building a ...Cartegraph
We are data rich and information poor--many companies have lived through the same challenges. We used to look at data in standard form and try to justify why things did not go the way they were planned and forecasted. We performed "autopsies on dead bodies but never brought them back to life, instead of finding a remedy for cure to deal with the future!"
Now we analyze data from multiple sources, establish patterns and cross references and then work on predictable models to allow Strategic Planning with a high degree of insight and proactive priority setting.
It's a mind shift and mind-set change that has taken a hold of the company and is pervasive down to the lowest level of planning. Constant change is what challenges us to continuously question our own models and improve in order to manage our business successfully.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Dashboards are Dumb Data - Why Smart Analytics Will Kill Your KPIsLuciano Pesci, PhD
Organizations of every size have access to data dashboard technology, yet none of the solutions have delivered on their hype and right now across the world executives and analysts are staring at a dashboard and thinking the same thing, ""so what?""
The failure of dashboards to deliver meaningful insights is inherent in their simplicity: they only show surface level information, and not the relationships between data points that really drive the fate of your organization.
But all is not lost! By combining the right mix of technology and human expertise in business strategy, research and data mining you can embrace the smart analytics movement, and start accessing insights that grow your company and your competitive position.
You can watch the accompanying webinar here: https://youtu.be/RdOcPxv9wLs
I presented this at ICT Spring Europe 2015 in Luxembourg. The presentation highlights the way in which big data investments are not always delivering on their promise and why brands should consider taking a 'human-centred' approach to big data analytics.
Does market information, marketing and consumer research have a role in busin...Drthomasbrand Limited
In this presentation, I review the status of information and research within companies, and discuss issues and constraints pertaining to the more effective use of information in business and marketing decision making. These touch upon the way in which research is managed in companies, as well as how it is viewed by the executive. To do it well, requires a mind-set change, even a cultural change in many executive teams and companies. Even the talk of "big data", is meaningless unless the company is receptive to the information and its eco-system is prepared for it.
Welcome to the Chief Analytics Officer Forum Europe
On 7th – 9th March 2016, over 80 Chief Analytics Officers and senior analytics leaders met in London for intimate, top-level discussions; dissecting the role of the CAO, exploring innovative case studies and addressing mutual cross-industry challenges. To learn more, visit http://www.caoforumeurope.com/
This event is organised by http://coriniumintelligence.com/
Creating a Data-Driven Organization, Data Day Texas, January 2016Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
Creating a Data-Driven Organization, Crunchconf, October 2015Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
These are slides from Ellen Wagner\'s featured theme presentation Making Learning Analytics Matter in the Educational Enterprise from Blackboard World 2012, New Orleasn, LA, July 12, 2012
From the MarTech Conference in London, UK, October 20-21, 2015. SESSION: The Human Side of Analytics. PRESENTATION: The Human Side of Data - Given by Colin Strong - @colinstrong - Managing Director - Verve, Author of Humanizing Big Data. #MarTech DAY2
The big-data explosion is driving a shift away from gut-based decision making. Marketing, in particular, is feeling the pressure to embrace new data-driven customer intelligence capabilities.
Marketers working 70-80 hours a week is not a great thing to hear.
But the requirement for them to have such a large amount of work time causes problems in the data selection and filtering.
Hence many marketers flunk the big data test
Where Data and Story Meet - Building the Data Storytelling CapabilityRanda McMinn
Data is rapidly transforming the way companies are transacting and engaging with customers. Gone are the days of not having enough data, now we are being inundated with too much data and are struggling to find ways to make sense of it. As a business leader, especially in the roles of data science and marketing, your success is heavily reliant on making sense of data, so it is becoming imperative to build and nurture a great data storytelling capability.
In this piece, we explore the increasing demands in skillsets for the modern data scientist and marketer. Further, we explore the mindset of data scientists and whether or not that mindset differs from a group of analytics professionals who have been identified as great data storytellers. We also reveal different ways to build the data storytelling capability.
Similar to Stop searching for elusive data scientist (20)
This presentation reports the statistical analysis of TED Talks. It reports various parameters which define the success of a TED Talk and similary failure of a TED Talk. It is the summary of the TED Talk "Lies, Damned Lies and Statistics" by Sebastian Wernicke
This presentation analyzes the HBR Article on "Big Data Hype (and Reality)" by Gregory Piatetsky-Shapiro. It emphasizes on the slow improvement of the technology, but in the end provides the areas where big data is useful.
This presentation analyzes the TED Talk by Sebastian Wernicke
on "How to use data to make a hit tv show". It analyzes the importance of logic in decision making rather than purely depending on data.
This presentation analyzes the TED Talk on "3 ways to spot a bad statistic" by Mona Chalabi. She emphasizes on asking 3 Questions whenever you come across any stats, to better understand the data.
The presentation analyzes the HBR article "A Predictive Analytics Primer" by Tom Davenport. It gathers insights on How can we predict better, with better assumptions.
This presentation describes the need to communicate Data.
It analyzes the HBR Article "Data is Worthless if You Don’t Communicate It" by Thomas H. Davenport.
This presentation analyzes the TED Talk by Susan Etlinger on "What do you do with all this big data". Gathering the insights and employing them are the two important things exhibited by the presentation.
The presentation talks about "Data Science being the sexiest job of the 21st century". What are the challenges faced by the industry and how to Overcome them, is the main theme of the presentation
This presentation analyses the beautiful TED Talk of Alan Smith on "Why should you love statistics". Gathering the insights and employing those insights is the major task of this presentation.
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.
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.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
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3. INSIGHT #1. Stop
hunting for that data
science unicorn and/or
silver bullet.
Odds are poor that you’ll
be able to find and hire
really good data
scientists.
4. • Surveys say there
simply aren’t enough
people with the unusual
blend of software skills
and statistical savvy to
go around.
• For many organizations,
a mediocre data
scientist may be worse
than none at all.
5. • Big organizations can
afford — or think they can
afford — to throw money at
the problem by hiring laid-
off Wall Street quants or
hiring big-budget analytics
boutiques.
• More frugal and prudent
enterprises seem to be
taking alternate
approaches.
6. INSIGHT #2.
Empowering small
cross-functional data-
oriented teams
• The teams must be explicitly
charged with delivering
tangible and measurable data-
driven benefits in relatively
short periods of time.
• The emphasis is on building
greater data capability than
better digital infrastructures.
7. • Data science must be a
cultural value, not just a
functional expertise.
• The goal is to make all of the
organization more
conversant in how to align
probability, statistics,
technology and business
value creation.
8. Even baby steps in analytics could yield large strides
in outcome.
11. Better Collection Understanding of the Employees
Better the
opportunities
to the team
Better
Relations
between the
staff.
Better learned
the workforce
will be
12. COST-SAVING FOR A
COMPANY
• Big savings deal for the
company by investing in small
teams, rather than hiring the
savvy quants.
• Limited ambition could do a
better job attracting credibility
and support than BHAGs.(Big
Hairy Audacious Goal)
13.
14. People don’t need to
become data scientists, but
they do need to understand
and appreciate key
principles and practices of
data science.
15. The temporary fix of
data science teaming
doesn’t solve the
problem, but it
creates the cultural
and organizational
context for the
necessary hires to
follow.