INDUSTRY INSIGHTS YOUR PEERS ARE READING
I’m a Software Engineer at Mixpanel, working on our data export pipeline. My focus is on making it as easy as possible to send the data you collect in Mixpanel, to your destination of choice. This pipeline sends your data to Redshift Spectrum, which is different than Redshift. MORE
EXABYTES of data daily. That’s 2,500,000 terabytes, or 2,500,000,000 gigabytes of data. So what is your company doing with all that data? So what is this data science thing? So how do I get at all this great data? And what can we do with data science? MORE
By Corey Reed, Head of Data Science & Satya Gandham, Machine Learning Engineering Manager When you serve millions of customers every year?—?averaging the opportunity to leverage all the data we have is ripe. A high-level view of our data architecture. There’s other data?—?like MORE
The Data / Information / Knowledge Paradox (Drawn From the DIKW Pyramid ). Data : data is feedback from your users, your market, or your product. Data is an input , and as such has no real value in itself, it tells you what is happening. Information: information is the output of data, after analysis. As such, the goal of data analysis is to find out why something is happening. In that sense, the gap from data to information is technical. MORE
Jenessa Lancaster is a data scientist at Ocado Technology. In this ProductTank London talk, she discusses the importance of communicating data concepts to non-specialist audiences. We live in promising times for data science in business development. Communicating Data Science. MORE
Below, I’ll share how I do this by using data to understand customer motivation. Sharpening design intuition with data. The perception is that there is an inherent conflict between creative intuition and data. I would say that data strengthens the intuition muscles. MORE
Your B2B data should be an asset on your balance sheet, not a liability. Making your data invaluable to your organization requires the right approach. To start with, improving the quality of your data is not a one-time event. B2B data MORE
Different organizations may have different ways to define the core job roles and key responsibility areas for their big data roles. While the roles of a Data Scientist and a Data Analyst may sound very alike, there are some core differentiators too. MORE
However, there are simply not enough data scientists in the world to deliver on the AI potential. Data scientists building AI applications require numerous skills – data visualization, data cleansing, artificial intelligence algorithm selection and diagnostics. MORE
Now, Indicative customers who use Snowplow will have the power to analyze their business data in real time. Snowplow’s open-source software already allows companies to collect rich and detailed event-based data about their customer journey. With real-time data, you can: 1. MORE
In Daniel Goddemeyer and Dominikus Baur we found the perfect partners for this, so we asked them to run an interactive data visualisation session immediately before the first coffee break. MORE
Mike Hyde leads data science and data engineering for Workplace, Facebook’s new enterprise product for company connectivity. He is passionate about using data and insights to create innovative company cultures, so he spoke at ProductTank London about data for growth. MORE
In this post I provide an introduction to the world of data acquisition and […] The post Data Acquisition: A Primer for IoT Product Managers appeared first on TechProductManagement. MORE
When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. To solve practical decision problems, the Data Scientist typically uses combinations of these methods. MORE
I decided to go for a short run on a neighboring track… Continue reading on Towards Data Science ». machine-learning data-science businessAs I was wrapping up my work last evening, darkness started to loom outside. MORE
Whether you are a seasoned data scientist or a business executive with a significant investment in analytics, chances are you’ve seen the… Continue reading on DataSeries ». data-science data-literacy MORE
“Big data.” It’s one of Silicon Valley’s favorite and most annoying buzzwords, yet there’s no data shortage in sight as data companies continue sprouting (and growing) like weeds. Not being a “math person” or a data scientist is no longer a valid excuse to diss data. MORE
One of these key focus areas is making the entire organization Data Literate. He believes developing Data Literacy across the organization would ultimately support the remaining three?—?customer-first We develop a year-long partnership of infusing data in the DNA of the organization. MORE
She had always enjoyed data and patterns. She finished her hands-on data science coursework in business analytics, A/B testing, and predictive analytics. She now knew experientially how powerful data science can be. career-paths career-change data-science careers career-advice MORE
Are you a Data Science hero?—?aka One day we started talking about Sherlock and what it would look like if Sherlock transitioned his career to become an analyst or data scientist? These days huge amounts of data?—?“Big Big Data”?—?overwhelm Are you a Data Science hero?—?aka MORE
Do you need to be able to code in R, Python, or any other programming language to put Data Science to work for you? analytics careers machine-learning business data-scienceThe answer is NO! Continue reading on DataSeries ». MORE
I run a Data Science Consulting company, and I say analytics consulting is a SCAM! In November 2017, Gartner released a report stating that 60% of big data projects fail. A Fortune Knowledge Group survey revealed that most of the 85% of the failure that Gartner reported were likely a result of executives’ tendency to trust their gut rather than data. I am passionate about using data to build better products and create amazing customer experiences. MORE
IoT products are known for producing large amounts of data. Some people even argue that the reason to deploy IoT products is to produce and collect all this data, that the data in itself is what provides the value. IoT and Big Data MORE
One of the challenges that we commonly run into as Product Managers is the battle between opinions and data. And though it would be nice to pretend that data always wins, and that there's always truth in Jim Barksdale's famous quote, "If we have data, let’s look at data. Let's talk about some common situations where data bends to opinion. MORE
Data is the world’s most valuable resource, according to The Economist, and the companies that primarily deal in data – Google, Amazon, Facebook and the like – are among the most valuable in the world. Data Moves to the Centre of the Value Proposition. MORE
I run a Data Science Consulting company, and I say analytics consulting is a SCAM! In November 2017, Gartner released a report stating that 60% of big data projects fail. A Fortune Knowledge Group survey revealed that most of the 85% of the failure that Gartner reported were likely a result of executives’ tendency to trust their gut rather than data. I am passionate about using data to build better products and create amazing customer experiences. MORE
Having reliable data available in real-time allows you to quickly and accurately sort through what is a valid concern and what is not, keep your team on task, and let data-driven product development reign. Let’s dig into three examples and look at how usage data can help. With usage data, you can quickly get a sense of just how pervasive the bug is, and what sort of effort needs to go into fixing it. Usage Data Sheds Light. MORE
“Big data” may be sexy, and quant research is great for. The post In Defense of Small Data appeared first on ProductCraft by Pendo. Perspectives Big data Interviews Qualitative research Research“How many people used our new feature last quarter?” MORE
This article draws on multiple sources to provide Product Manager salary data. Trulia data shows the same average of $113k, but also indicates that the average for a Product Manager in the San Francisco area is $140k. MORE
Chris shares real-world examples and lessons learned as User Testing established its Product Insights team, a team which is made up of UX researchers, data scientists and data engineers. Most companies’ user research and data science teams work separately. MORE
Keeping track of how customers are interacting with their brands, and how long products are taking to catch on with audiences traditionally requires data teams to conduct lengthy analysis. So, here are five ways to foster data literacy across the organization. MORE
Qualitative versus quantitative data: we’ve all been involved in a conversation debating their respective merits at some point in our careers. So which type of data is better? Another angle is the softness and hardness of the data. We’ll need more soft data to find the answer. MORE
Keeping track of how customers are interacting with their brands, and how long products are taking to catch on with audiences traditionally requires data teams to conduct lengthy analysis. So, here are five ways to foster data literacy across the organization. MORE
Data Related Topics Piyanka Jain
MARCH 29, 2019
One of these key focus areas is making the entire organization Data Literate. He believes developing Data Literacy across the organization would ultimately support the remaining three?—?customer-first We develop a year-long partnership of infusing data in the DNA of the organization.
Mind the Product
APRIL 24, 2019
Jenessa Lancaster is a data scientist at Ocado Technology. In this ProductTank London talk, she discusses the importance of communicating data concepts to non-specialist audiences. We live in promising times for data science in business development. Communicating Data Science.
Piyanka Jain
MAY 9, 2019
I run a Data Science Consulting company, and I say analytics consulting is a SCAM! In November 2017, Gartner released a report stating that 60% of big data projects fail. A Fortune Knowledge Group survey revealed that most of the 85% of the failure that Gartner reported were likely a result of executives’ tendency to trust their gut rather than data. I am passionate about using data to build better products and create amazing customer experiences.
Piyanka Jain
MAY 9, 2019
I run a Data Science Consulting company, and I say analytics consulting is a SCAM! In November 2017, Gartner released a report stating that 60% of big data projects fail. A Fortune Knowledge Group survey revealed that most of the 85% of the failure that Gartner reported were likely a result of executives’ tendency to trust their gut rather than data. I am passionate about using data to build better products and create amazing customer experiences.
Piyanka Jain
MAY 2, 2019
Do you need to be able to code in R, Python, or any other programming language to put Data Science to work for you? analytics careers machine-learning business data-scienceThe answer is NO! Continue reading on DataSeries ».
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DemandMatrix
MAY 21, 2019
Different organizations may have different ways to define the core job roles and key responsibility areas for their big data roles. While the roles of a Data Scientist and a Data Analyst may sound very alike, there are some core differentiators too.
280 Group
FEBRUARY 22, 2019
This article draws on multiple sources to provide Product Manager salary data. Trulia data shows the same average of $113k, but also indicates that the average for a Product Manager in the San Francisco area is $140k.
Piyanka Jain
APRIL 23, 2019
Are you a Data Science hero?—?aka One day we started talking about Sherlock and what it would look like if Sherlock transitioned his career to become an analyst or data scientist? These days huge amounts of data?—?“Big Big Data”?—?overwhelm Are you a Data Science hero?—?aka
Mind the Product
APRIL 23, 2019
The Data / Information / Knowledge Paradox (Drawn From the DIKW Pyramid ). Data : data is feedback from your users, your market, or your product. Data is an input , and as such has no real value in itself, it tells you what is happening. Information: information is the output of data, after analysis. As such, the goal of data analysis is to find out why something is happening. In that sense, the gap from data to information is technical.
Speaker: Azmat Tanauli, Senior Director of Product Strategy at Birst
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Mixpanel
APRIL 24, 2019
I’m a Software Engineer at Mixpanel, working on our data export pipeline. My focus is on making it as easy as possible to send the data you collect in Mixpanel, to your destination of choice. This pipeline sends your data to Redshift Spectrum, which is different than Redshift.
Piyanka Jain
APRIL 2, 2019
She had always enjoyed data and patterns. She finished her hands-on data science coursework in business analytics, A/B testing, and predictive analytics. She now knew experientially how powerful data science can be. career-paths career-change data-science careers career-advice
UserVoice
JUNE 21, 2017
“Big data.” It’s one of Silicon Valley’s favorite and most annoying buzzwords, yet there’s no data shortage in sight as data companies continue sprouting (and growing) like weeds. Not being a “math person” or a data scientist is no longer a valid excuse to diss data.
Mind the Product
FEBRUARY 25, 2019
Mike Hyde leads data science and data engineering for Workplace, Facebook’s new enterprise product for company connectivity. He is passionate about using data and insights to create innovative company cultures, so he spoke at ProductTank London about data for growth.
Birst BI
NOVEMBER 20, 2018
When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. To solve practical decision problems, the Data Scientist typically uses combinations of these methods.
Piyanka Jain
FEBRUARY 27, 2019
Ironically… Continue reading on Towards Data Science ». data-science analytics education business careersRecently I have been mentoring fresh graduates of the Masters in Business Analytics program from a historic Virginia school.
Piyanka Jain
FEBRUARY 20, 2019
I decided to go for a short run on a neighboring track… Continue reading on Towards Data Science ». machine-learning data-science businessAs I was wrapping up my work last evening, darkness started to loom outside.
Birst BI
AUGUST 23, 2018
However, there are simply not enough data scientists in the world to deliver on the AI potential. Data scientists building AI applications require numerous skills – data visualization, data cleansing, artificial intelligence algorithm selection and diagnostics.
Speaker: Ian Thompson, Head of Business Intelligence at King, and Zara Wells, Strategic Customer Success Manager at Looker
Product Managers looking to leverage data to make informed product design decisions can learn a lot from renowned gaming company King, maker of Candy Crush and many other games - even if their product has seemingly no overlap with games. Don't miss King’s data expert (dare we say king?)
Mind the Product
FEBRUARY 13, 2018
Data is the world’s most valuable resource, according to The Economist, and the companies that primarily deal in data – Google, Amazon, Facebook and the like – are among the most valuable in the world. Data Moves to the Centre of the Value Proposition.
Mind the Product
JANUARY 10, 2018
Qualitative versus quantitative data: we’ve all been involved in a conversation debating their respective merits at some point in our careers. So which type of data is better? Another angle is the softness and hardness of the data. We’ll need more soft data to find the answer.
Pragmatic Marketing
FEBRUARY 15, 2019
EXABYTES of data daily. That’s 2,500,000 terabytes, or 2,500,000,000 gigabytes of data. So what is your company doing with all that data? So what is this data science thing? So how do I get at all this great data? And what can we do with data science?
Mind the Product
DECEMBER 4, 2017
Having reliable data available in real-time allows you to quickly and accurately sort through what is a valid concern and what is not, keep your team on task, and let data-driven product development reign. Let’s dig into three examples and look at how usage data can help. With usage data, you can quickly get a sense of just how pervasive the bug is, and what sort of effort needs to go into fixing it. Usage Data Sheds Light.
Speaker: Tristan Kromer, Lean Agile Coach, Kromatic
Qualitative data from UXers should not compete against the quantitative data product owners need for their business model. Qualitative vs. Quantitative is a silly argument.
Daniel Elizalde IoT Blog
DECEMBER 13, 2017
In this post I provide an introduction to the world of data acquisition and […] The post Data Acquisition: A Primer for IoT Product Managers appeared first on TechProductManagement.
ProductCraft
DECEMBER 4, 2018
“Big data” may be sexy, and quant research is great for. The post In Defense of Small Data appeared first on ProductCraft by Pendo. Perspectives Big data Interviews Qualitative research Research“How many people used our new feature last quarter?”
Mixpanel
APRIL 12, 2019
Below, I’ll share how I do this by using data to understand customer motivation. Sharpening design intuition with data. The perception is that there is an inherent conflict between creative intuition and data. I would say that data strengthens the intuition muscles.
Mind the Product
FEBRUARY 7, 2018
Chris shares real-world examples and lessons learned as User Testing established its Product Insights team, a team which is made up of UX researchers, data scientists and data engineers. Most companies’ user research and data science teams work separately.
Speaker: Cait Porte, SVP Product and Customer Experience, Zmags
Join Product Management expert Cait Porte as she covers how to sell your ideas internally by leveraging data to drive decision making. During this discussion, we'll talk through: Leveraging data to make feature decisions.
Daniel Elizalde IoT Blog
AUGUST 1, 2017
IoT products are known for producing large amounts of data. Some people even argue that the reason to deploy IoT products is to produce and collect all this data, that the data in itself is what provides the value. IoT and Big Data
StubHub
FEBRUARY 21, 2019
By Corey Reed, Head of Data Science & Satya Gandham, Machine Learning Engineering Manager When you serve millions of customers every year?—?averaging the opportunity to leverage all the data we have is ripe. A high-level view of our data architecture. There’s other data?—?like
Clever PM
AUGUST 16, 2018
One of the challenges that we commonly run into as Product Managers is the battle between opinions and data. And though it would be nice to pretend that data always wins, and that there's always truth in Jim Barksdale's famous quote, "If we have data, let’s look at data. Let's talk about some common situations where data bends to opinion.
Mind the Product
AUGUST 22, 2018
In Daniel Goddemeyer and Dominikus Baur we found the perfect partners for this, so we asked them to run an interactive data visualisation session immediately before the first coffee break.
Speaker: Nils Davis, Principal, NPD Associates
Usage data allows PMs, the product team, and the whole organization to make better decisions. But what if you don't have that data - such as before you have users? Or, what if the right decision seems to fly in the face of the data you have?
Indicative
SEPTEMBER 19, 2018
Now, Indicative customers who use Snowplow will have the power to analyze their business data in real time. Snowplow’s open-source software already allows companies to collect rich and detailed event-based data about their customer journey. With real-time data, you can: 1.
Indicative
SEPTEMBER 4, 2018
Keeping track of how customers are interacting with their brands, and how long products are taking to catch on with audiences traditionally requires data teams to conduct lengthy analysis. So, here are five ways to foster data literacy across the organization.
Indicative
SEPTEMBER 7, 2018
Keeping track of how customers are interacting with their brands, and how long products are taking to catch on with audiences traditionally requires data teams to conduct lengthy analysis. So, here are five ways to foster data literacy across the organization.
DemandMatrix
FEBRUARY 22, 2018
Your B2B data should be an asset on your balance sheet, not a liability. Making your data invaluable to your organization requires the right approach. To start with, improving the quality of your data is not a one-time event. B2B data
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