For Data Scientists, Big Data is not so Big
FEBRUARY 15, 2016
In our study of data scientists, we found that only about a third of them possessed skills needed to handle big and distributed data. These results are in line with findings from other studies that find that data scientists typically analyze small data sets. Top Data Science Skills by Job Role. Size of Data Sets. Adoption of Big Data. Figure 1.
The Data Economy Is Going To Be Huge. Believe Me.
Forrester's Customer Insights
FEBRUARY 3, 2017
I've just finished reading the recent Communication on Building a European Data Economy published by the European Commission. I'm in the thick of my research for a new report on data commercialization. When I first published It's Time To Take Your Data To Market the idea was merely a twinkle in people's eye. big data. data economy. Are they serious?
Investigating Data Scientists, their Skills and Team Makeup
SEPTEMBER 23, 2015
A new survey of 490 data professionals from small to large companies, conducted by AnalyticsWeek in partnership with Business Over Broadway, provides a look into the field of data science. Download the free Executive Summary of the report, Optimizing your Data Science Teams. . Many pundits have offered their take on what it takes to be a successful data scientist.
Top 10 Skills in Data Science
JANUARY 4, 2016
The practice of data science requires skills that fall into three general areas: business acumen, computer technology/programming and statistics/math. Dave Holtz describes the data science skills you need to get a job as a data scientist ( 8 Skills You Need to Be a Data Scientist ). Data Science Skills and Possessing Proficiency in the Skills. Figure 1. Figure 2.
The rise and fall of big data hype—and what it means for customer intelligence
JULY 28, 2016
The following is an excerpt from the e-book Big Data and Beyond. To learn more about this topic, join us at the 2016 Customer Intelligence Summit , where Lauren Meewes, senior program manager of seller at eBay, and Catherine Makk, vice president of global insights at HarperCollins, will share how to use customer feedback to give context and meaning to big data. The rise of big data.
When Does Education Level Matter in Data Science?
MARCH 14, 2016
Data scientists are highly educated. In our study of data scientists, we found that over half of them, both men and women , hold either a Masters or PhD degree and about a quarter of them hold a 4-year degree. Data scientists have the hottest jobs in America this year. Due to a shortage of these data-savvy people, data scientists are in high demand and well-paid.
Data Scientists and the Practice of Data Science
NOVEMBER 16, 2015
I was recently involved in a couple of panel discussions on what it means to be a data scientist and the practice of data science. Moderated by Brian Fanzo , the panel included me and these data experts: Andrew C. Oliver , President of Mammoth Data. Lillian Pierson of Data-Mania. I enjoyed our discussions and their take on the topic of data science.
Customer retention: 35 data-backed approaches
JUNE 23, 2016
I talk often about customer experience , but recently I’ve heard from some followers that they’d like a bit more on customer retention. The first thing to understand about customer retention is that obviously it comes straight from customer experience. In short, if the customer experience is good, the customer retention is there. Also there: referral. Strategy: The recovery call.
Insights Services Drive Data Commercialization
Forrester's Customer Insights
MARCH 8, 2017
The new data economy isn't about data; it is about insights. A growing number of companies recognize the opportunity their data provides, and they take that data to market: 1/3 of firms report commercializing data or sharing it for revenue with partners or customers. Read more Categories: big data. data commercialization. data economy.
Big Data: Is Customer Service Ready for It?
JUNE 23, 2015
3 Steps to Prepare Customer Service for Big Data A very interesting blog post by Bernard Marr demystifying big data defines its essence and explains the extensive global influence and boundless benefits that can be derived. Big data also has many possibilities in elevating customer experience to new heights. Is customer service ready for big data? But will it?
10 Data Science Skills You Need to Improve Project Success
JANUARY 11, 2016
Last week, I identified the top skills across different data science professionals. The results of our survey of 620+ data professionals showed that, while data scientists possess many different skills (we looked at 25 skills), some skills are more popular/common to data scientists compared to other skills. Frequency vs. Importance of Data Science Skills. Table 2.
Skill-Based Approach to Improve the Practice of Data Science
NOVEMBER 30, 2015
Our Big Data world requires the application of data science principles by data professionals. I've recently taken a look at what it means to practice data science as a data scientist. Our survey results of over 500 data professionals revealed that different types of data scientists possess proficiency in different types of data skills.
What's My Data Worth?
Forrester's Customer Insights
OCTOBER 11, 2016
I know I'm sitting on valuable data but I'm not sure just how valuable. When it comes to using the data internally to improve operational efficiency or service delivery, the resulting cost savings demonstrates the value. Or when using the data to identify new customer opportunities, either upsell to existing customers or identifying potential new customers, the resulting revenue generated demonstrates the value. But what if I want to take the data to market? What's the data worth? The Value of Data. data economy. Think back to a math course.
Getting Insights Using Data Science Skills and the Scientific Method
OCTOBER 23, 2015
The event will, no doubt, help companies understand how to use analytics to get insight from their data. As a first step in sharing my knowledge about how to get insight from data, IBM asked me what I thought about the role of the data scientist in the Insight Economy. Generally speaking, I think that the role of data scientists is to extract value from data.
?Big Data – The Case for Customer Experience
AUGUST 9, 2016
Big Data is back on the corporate agenda. exabytes of data were created every day; by 2014 this was 2.3 I say ‘back’, it never went away for the CIO, it’s just moving with the times, bumped along by changes in operating systems, user technologies and digital transformation. In 2013 IBM reported over 2.5 zettabytes. View Article
Why Data Science Needs Subject Matter Expertise: Data Have Meaning
FEBRUARY 1, 2016
In our Big Data world , we are awash in data. Volume, Velocity and Variety) represent significant hurdles to businesses in their race to extract value from their data. The Meaning of Your Data. Data are more than a string of numbers. Ensuring your data represents something meaningful to your business is essential to finding value from your data. The meaning of numbers is about the veracity of your data. It's no wonder that subject matter expertise is one of the three pillars of data science. We have a lot of it. Those three Vs (i.e.,
3 Ways Integrated Analytics Can Solve Your Data Nightmare
MAY 3, 2016
When it comes to making operations more efficient, most executives know they need to leverage data to identify areas of improvement. Data collection and storage is manageable, but executives can easily find themselves with a mountain of information and more questions than answers. One option is to hire a team of highly trained data scientists to dig through the data.
Keeping Up with the Data Eruption
JUNE 8, 2016
7 Ways to Make Sure You’re Getting the Most of Your Unstructured Data with Text Analytics Today and Tomorrow Yesterday my 10-year-old daughter sent 43 text messages, posted 8 Musical.ly videos, and put up two new Instagram posts. And given the fact she spent 8 hours at school and 4 hours at gymnastics practice, that. View Article
[Infographic] A Quick Guide to Customer Data
FEBRUARY 22, 2017
In the world of SaaS, there certainly isn't a lack of data. In order to activate and leverage customer data for success, you need to start not only by collecting data but by collecting the right data. The customer data you collect and leverage has a great impact on success: that of your team, that of your customer, and that of your company at large.
China Unicom Monetizes Customer Behavior Data
Forrester's Customer Insights
JULY 20, 2015
China Unicom demonstrated its big data analytics platform, including customer analytics, during the Shanghai World Mobile Congress last week. Huawei is helping China Unicom's Shanghai affiliate build a big data analytics platform that can collect and analyze customer demographics and operational and behavioral data. big data. digital analytics. mobile analytics.
Improving Gender Diversity in Data Science
DECEMBER 7, 2015
Results of a survey of data professionals show that about 1 out of 4 data scientists are women. Both women and men have similar levels of education and proficiency in data science skills. Ways of improving gender diversity in the field of data science are offered. Gender Diversity in Data Science. Gender differences in Data Science Job Roles. Figure 1.
Getting More Insights from Data: Nine Facts about the Practice of Data Science
DECEMBER 14, 2015
The value of data is measured by what you do with it, and organizations are relying on data scientists to extract that value. I recently conducted a survey of data professionals to better understand what it means to be a data scientist. I discovered a few things that can help organizations optimize the value of their data. Facts about Data Science. Summary.
Making Sense of Our Big Data World: Samples, Populations and Sampling Error
JANUARY 25, 2016
As part of my series on Making Sense of Our Big Data World, today's post is on sampling error. See the overview, Making Sense of Our Big Data World: Statistics for the 99% , to understand the importance and value of understanding statistics and statistical thinking. From the large data set, we create smaller, homogeneous, data sets to make predictions within smaller groups.
Statistics: Is This Big Data’s Biggest Hurdle?
MARCH 28, 2015
Big Data is less about the data itself and more about what you do with the data. The application of statistics and statistical principles on the data helps you extract the information it contains. According to Wikipedia , statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. Statistics is the language of data.
The Future is Now: Take Your Customer Data to the Next Level
JANUARY 11, 2017
Data is available in abundance these days. There are a ton of statistics out there about the volume of data we see today vs. just a few years ago, but I think we can all agree that there's a lot of it! I've written previously about the six steps you should take to use data to transform the customer experience. Companies are sitting on a goldmine of data. Which tools?
How IBM is Transforming Data Science
FEBRUARY 24, 2016
I was invited by IBM as a guest to share some insights from the perspective of a data scientist. Data science is about extracting insights from data. One way that data scientists are helping people get value from data is by creating mobile applications that aggregate, summarize and present data in meaningful and useful ways to the end user.
Maximizing the Impact of Data Science Using the Scientific Method
FEBRUARY 29, 2016
We live in a Big Data world where everything is being quantified. As a result, businesses are trying to make sense of their ever-expanding, diverse, streaming data sources to drive their business forward. If your competitors have access to the same type of data (CRM, ERP, weather, etc.) One way is to get better insights from your data. Data Science Skills.
Shocking! Yahoo’s data breach
SEPTEMBER 28, 2016
That was over two years ago—ironically around the same time as the Yahoo Data breach. Later, when Yahoo account holders think of the brand, they will remember feeling afraid, angry and disappointed that it lost their data to hackers, where it ended up on the black market. Whether Yahoo is to blame or mishandled the data is yet unknown. How we feel affects how we behave.
The Data Privacy Challenge – Is Your CX Program Ready?
NOVEMBER 4, 2015
On the other hand, personal data and data-protection regulations are becoming more restrictive. Two very divergent trends are coming to a head, which could potentially change the way the industry does business. On one hand, CX programs and customer needs are more targeted towards a dialogue with the individual customer. This collision means businesses are. View Article
Empirically-Based Approach to Understanding the Structure of Data Science
JANUARY 18, 2016
Based on a study of 620+ data professionals, we found that data science skills fall into three broad areas: domain expertise (in our case, business), technology/programming and math/statistics. I discuss the implications of study findings for current data scientists, would-be data scientists and the recruiters who try to find them. The Structure of Data Science Skills.
Four Ways Big Data Can Improve Customer Surveys
MAY 4, 2015
Big Data. They provide the data that fuel the customer experience analytics that generate the customer insights to drive the business forward. In this new Big Data world , however, it’s clear that businesses are now able to use different sources of data (e.g., Businesses, having access to so much data, can easily get lost in a cycle of never-ending analysis.
Do you know where your data is?
JANUARY 16, 2017
One of the biggest challenges CX practitioners face is uncovering actionable data that will help improve the customer experience. Often company structure and culture play a big role in determining how hard/easy it is to dig out the data. So where do CX and CEM professionals get actionable data to make intelligent decisions? So where are the data sources? NPS/CSAT.
Sell the Value of Data Insights to the C-Suite
JULY 12, 2016
The key to unlocking this power is the insight provided by data analytics. There are three primary points to cover when selling the value of data insights to the C-suite: Outline the functionality and benefits of using analytics. Beyond the understanding of what the data insights of WFO can do, it is important to translate the functionality into results.
Optimizing Sales Compensation using Big Data
DECEMBER 8, 2016
Sales compensation is a world swamped with data. ICM applications must accommodate a wide variety of data from upstream systems, facilitate processing, and deliver results through multiple channels and formats in order to support activities such as territory management, quota setting, modeling, forecasting, commission calculation, and on-demand reporting and analysis
Assess Your Data Science Expertise
AUGUST 31, 2015
What kind of a data scientist are you? Take the free Data Skills Scoring System Survey at [link]. Data science skills. Companies rely on experts who can make sense of their data. Often referred to as data scientists, these people bring their specific skills to bear in helping extract insight from the data. Complementary Data Skills Required.
Data Science Talent is Key to Analytical Innovators
JULY 1, 2015
One way they are trying to get ahead is through the application of analytics on their data. Companies need the right people with the right data science skills (i.e., data workers) to make sense of the data. In their continuing study of analytics, MIT and SAS recently published new research about how Analytic Innovators optimize their data science capabilities.
Forrester’s 2016 Predictions: All That Data Will Finally Drive Business Action
Forrester's Customer Insights
NOVEMBER 9, 2015
Do you consider yourself "data-driven"? But the reality is that most businesses have only scratched the surface when it comes to transforming all of that data into insight that drives real business action. and I predict what will happen in the hottest areas of big data, analytics, business intelligence, and systems of insight -- and tell you what to do about it. Here's a sneak at just a few highlights: Read more Categories: #big data. Big Data; Advanced analytics; analytics; Internet of Everything; video analytics; data virtualization; digital intelligence.