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.
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. 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. .
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 ).
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. The big data hype is officially dead. In 2015, the analyst firm Gartner dropped big data from its Hype Cycle for Emerging Technologies report. The rise of big data. The big drawback 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.
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.
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.
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. Is customer service ready for big data?
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. For example, the top two skills were communication and managing structured data while the bottom two skills were big and distributed data and cloud management. S - Data Management (.33).
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.
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. Substandard Proficiency in Data Skills. Data Mining. Data Mining.
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?
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.
?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.
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.
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
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. Such data is unique and even more comprehensive than that generated by Internet service giants like Baidu, Alibaba, or Tencent. big data.
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.
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. Facts about Data Science.
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.
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. We have a lot of data and are generating a lot more of it.
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. The platform allows programmers to can get access to any of the data sets via an API to help them develop products.
[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 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! Companies are sitting on a goldmine of data.
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.)
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.
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. 25 Data Science Skills Assessed in the Data Science Survey.
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.,
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.
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 are the data sources?
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.
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. Complementary Data Skills Required. Data Skills Scoring System (DS3).
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
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. Data Scientist Role a Sign of Analytical Maturity.
Choose the Right Customer Experience Data to Make a Difference
MARCH 21, 2017
Big data can be overwhelming. And while customer experience management (CEM) activities should be data-driven, it is hard to figure out which data to use. Every industry, and every company, will have different types of data to look at. It’s just…well, big.