Data Literacy 101

Piyanka Jain

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.

Talking About Data Science by Jenessa Lancaster

Mind the Product

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.

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Data Science Consulting Is A SCAM!

Piyanka Jain

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.

Data Science Consulting Is A SCAM!

Piyanka Jain

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.

Top 10 industries for monetizing data: Is yours one of them?

Is programming a must for applying Data Science?

Piyanka Jain

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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Top Skills Required in every Data Scientist and Data Analyst

DemandMatrix

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.

Product Manager Salary Data in 2019

280 Group

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.

Are you a Data Science hero?—?aka BADIRist?

Piyanka Jain

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

Why Data is key in Building a Company That Learns

Mind the Product

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.

Embedded BI and Analytics: Best Practices to Monetize Your Data

Speaker: Azmat Tanauli, Senior Director of Product Strategy at Birst

Why you’re better off exporting your data to Redshift Spectrum, instead of Redshift

Mixpanel

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.

An Engineer’s Journey To Become A Data Scientist

Piyanka Jain

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

Here’s Why Every Product Manager Must Learn to Love Data

UserVoice

“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.

Unlocking Data Science to Build the Future of Work by Mike Hyde

Mind the Product

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.

Nine companies share 30+ best practices for creating embedded analytics products

Inside the Mind and Methodology of a Data Scientist

Birst BI

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.

Top 5 FAQ On Mastering Data Science And Making Your Career Transition

Piyanka Jain

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.

What 2 Men And a Runner Taught Me About Data Science and Fraud Modeling

Piyanka Jain

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.

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What AI Means to a Data Scientist

Birst BI

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.

How King Crushes New Product Development using Data-Driven Insights

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?)

The Fundamentals of Building Better Data Products

Mind the Product

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.

Why you Need Quantitative AND Qualitative Data

Mind the Product

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.

Data Science for Business Professionals

Pragmatic Marketing

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?

3 Ways to Enlist Your Usage Data to Drive Product Development

Mind the Product

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.

Mixing Qualitative & Quantitative Data with Storyboarding

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.

Data Acquisition: A Primer for IoT Product Managers

Daniel Elizalde IoT Blog

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.

In Defense of Small Data

ProductCraft

“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?”

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How data informs design intuition

Mixpanel

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.

Why Data Science and UX Research Teams are Better Together

Mind the Product

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.

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Selling Data and Decisions to your Team

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.

How to Differentiate Your IoT Product: Provide Insights Not Data

Daniel Elizalde IoT Blog

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

Creating the Ultimate Data Orchestrator

StubHub

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

Data v. Opinion: The Ultimate Battle

Clever PM

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.

Let’s Engage – Live Data Visualisation at MTP Engage Hamburg 2018

Mind the Product

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.

What Users Want: How and Why to Build Knowledge into Your Product

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?

5 Ways Real-Time Data Can Make Your Business More Efficient

Indicative

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.

Five Ways to Foster Data Literacy Across the Organization

Indicative

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.

5 Ways to Foster Data Literacy Across the Organization

Indicative

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.

B2B data: 4 critical factors to improve data quality

DemandMatrix

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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Top 5 Analytics Features to Reach More Users with Valuable Data Insights