{"id":1789,"date":"2019-06-14T08:29:25","date_gmt":"2019-06-14T15:29:25","guid":{"rendered":"https:\/\/www.springboard.com\/?p=1789"},"modified":"2023-07-08T17:24:18","modified_gmt":"2023-07-09T00:24:18","slug":"41-shareable-data-quotes","status":"publish","type":"post","link":"https:\/\/www.springboard.com\/blog\/data-analytics\/41-shareable-data-quotes\/","title":{"rendered":"41 Shareable Data Quotes That Will Change How You Think About Data"},"content":{"rendered":"\n

The amount of data generated in real time is immense. This has created oceans of data from which companies can derive real business value and make better business decisions. The big data market is predicted to grow by 20% this year, and by 2020, every human is expected to generate 1.7 megabytes (of data) every second. The big data and analytics market will be worth $103 billion by 2023. <\/span><\/p>\n\n\n\n

It\u2019s important because making smart business decisions saves organizations a lot of money while helping them identify new opportunities to generate revenue. For example, leveraging big data is already saving <\/span>Netflix<\/span><\/a> as much as a $1 billion a year on customer retention. <\/span><\/p>\n\n\n\n

If you\u2019re thinking about embarking on a data science career<\/a>, you might want to read up on what the experts have to say about it. Some may reinforce what you already believe while others may change how you think about data completely.<\/span><\/p>\n\n\n\n

You don\u2019t even have to conduct a Google search because we did all the work and curated this list of 41 data quotes.<\/span><\/p>\n\n\n\n

Data Quotes: Why Data Is Important<\/h2>\n\n\n\n
\"Data<\/figure>\n\n\n\n

Big data and analytics are at the core of making intelligent business decisions. However, to make those decisions, it\u2019s critical to clean data, process it, and manage it efficiently (to derive valuable insights). The data quotes below underscore the importance of data and data analytics<\/a> in a digitally transformed world:<\/span><\/p>\n\n\n\n

1. \u201cMost of the world will make decisions by either guessing or using their gut. <\/span>They will be either lucky or wrong<\/span><\/a>.\u201d – <\/span>Suhail Doshi<\/span><\/a>, chief executive officer, Mixpanel<\/a>.<\/span><\/em><\/p>\n\n\n\n

2. “We are moving slowly into an era where big data is the starting point, not the end.” – <\/span>Pearl Zhu<\/span><\/a>, author of the \u201c<\/span>Digital Master<\/span><\/a>\u201d book series.<\/span><\/em><\/p>\n\n\n\n

3. \u201cWithout big data, you are <\/span>blind and deaf in the middle of a freeway<\/span><\/a>.\u201d – <\/span>Geoffrey Moore<\/span><\/a>, management consultant and theorist.<\/span><\/em><\/p>\n\n\n\n

4. \u201cWe\u2019re entering a new world in which data may be more important than software.\u201d – <\/span>Tim O\u2019Reilly<\/span><\/a>, founder, <\/span>O\u2019Reilly Media<\/span><\/a>.<\/span><\/em><\/p>\n\n\n\n

5. \u201c<\/span>Statistics are like bikinis<\/span><\/a>. What they reveal is suggestive, but what they conceal is vital.\u201d – <\/span>Aaron Levenstein<\/span><\/a>, business professor at Baruch College.<\/span><\/em><\/p>\n\n\n\n

6. \u201cInformation is the <\/span>oil of the 21st century<\/span><\/a>, and analytics is the combustion engine.\u201d – <\/span>Peter Sondergaard<\/span><\/a>, senior vice president, Gartner Research. <\/span><\/em><\/p>\n\n\n\n

7. \u201c<\/span>Data scientists are involved with gathering data<\/span><\/a>, massaging it into a tractable form, making it tell its story, and presenting that story to others.\u201d – <\/span>Mike Loukides<\/span><\/a>, editor, O\u2019Reilly Media.<\/span><\/em><\/p>\n\n\n\n

8. \u201cA data scientist is someone who can obtain, scrub, explore, model, and interpret data, blending hacking, statistics, and machine learning. Data scientists not only are adept at working with data, <\/span>but appreciate data itself as a first-class product<\/span><\/a>.\u201d – <\/span>Hillary Mason<\/span><\/a>, founder, Fast Forward Labs.<\/span><\/em><\/p>\n\n\n\n

9. \u201cThink analytically, rigorously, and systematically about a business problem and come up with a <\/span>solution that leverages the available data<\/span><\/a>.\u201d – <\/span>Michael O\u2019Connell<\/span><\/a>, chief analytics officer, TIBCO.<\/span><\/em><\/p>\n\n\n\n

10. \u201cThe goal is to turn data into information and <\/span>information into insight<\/span><\/a>.\u201d \u2013 <\/span>Carly Fiorina<\/span><\/a>, former chief executive officer, Hewlett Packard.<\/span><\/em><\/p>\n\n\n\n

Data Quotes: The Challenges of Adopting Data and Analytics<\/h2>\n\n\n\n
\"Data<\/figure>\n\n\n\n

When an enormous amount of structured and unstructured data is generated in real time, things can get complicated very quickly. But it\u2019s crucial to overcome the challenges related to the adoption of data and analytics as it can potentially lead to new business opportunities, enhanced efficiency, and significant savings. The following data quotes provide real-world examples of how companies handle it:<\/span><\/p>\n\n\n\n

11. \u201cWhat we found challenging, and what I find in my discussions with a lot of my counterparts that is still a challenge, is finding the set of tools<\/a> that enable organizations to efficiently generate value through the process. I hear about individual wins in certain applications, but having a more sort of cohesive ecosystem in which this is fully integrated is something that I think we are all struggling with, in part because it\u2019s still very early days. Although we\u2019ve been talking about it seemingly quite a bit over the past few years, <\/span>the technology is still changing<\/span><\/a>; the sources are still evolving.\u201d – <\/span>Ruben Sigala<\/span><\/a>, former EVP and chief marketing officer, Caesars Entertainment.<\/span><\/em><\/p>\n\n\n\n

12. \u201cThe biggest challenge of making the evolution from a knowing culture to a learning culture\u2014from a culture that largely depends on heuristics<\/a> in decision making to a culture that is much more objective and data-driven and <\/span>embraces the power of data and technology<\/span><\/a>\u2014is really not the cost. Initially, it largely ends up being imagination and inertia\u2026 What I have learned in my last few years is that the power of fear is quite tremendous in evolving oneself to think and act differently today, and to ask questions today that we weren\u2019t asking about our roles before. And it\u2019s that mindset change\u2014from an expert-based mindset to one that is much more dynamic and much more learning oriented, as opposed to a fixed mindset\u2014that I think is fundamental to the sustainable health of any company, large, small, or medium.\u201d – <\/span>Murli Buluswar<\/span><\/a>, chief science officer, AIG.<\/span><\/em><\/p>\n\n\n\n

13. \u201cEvery day, three times per second, <\/span>we produce the equivalent<\/span><\/a> of the amount of data that the Library of Congress has in its entire print collection, right? But most of it is like cat videos on YouTube or 13-year-olds exchanging text messages about the next Twilight movie.\u201d – <\/span>Nate Silver<\/span><\/a>, founder and editor in chief of FiveThirtyEight.<\/span><\/em><\/p>\n\n\n\n

14. \u201cThe human side of analytics is the <\/span>biggest challenge to implementing big data<\/span><\/a>.\u201d – <\/span>Paul Gibbons<\/span><\/a>, author of \u201cThe Science of Successful Organizational Change.\u201d<\/span><\/em><\/p>\n\n\n\n

15. \u201cOne of the biggest challenges is around data privacy and what is shared versus what is not shared. And my perspective on that is consumers are willing to share if there\u2019s value returned. One-way sharing is not going to fly anymore. So how do we protect and how do we harness that information and become a partner with our consumers rather than kind of just a vendor for them?\u201d – <\/span>Zoher Karu<\/span><\/a>, head of data and analytics, APAC and EMEA.<\/span><\/em><\/p>\n\n\n\n

16. \u201cThe first change we had to make was just to make our data of higher quality. We have a lot of data, and sometimes we just weren\u2019t using that data, and we weren\u2019t paying as much attention to its quality as we now need to\u2026 The second area is working with our people and making certain that we are centralizing some aspects of our business. We are centralizing our capabilities, and we are democratizing its use. I think the other aspect is that we recognize as a team and as a company that we ourselves do not have sufficient skills, and we require collaboration across all sorts of entities outside of American Express. This collaboration comes from technology innovators, it comes from data providers, it comes from analytical companies. We need to put a full package together for our business colleagues and partners so that it\u2019s a convincing argument that we are developing things together, that we are co-learning, and that we are building on top of each other.\u201d – <\/span>Ash Gupta<\/span><\/a>, former American Express executive; president, Payments and E-Commerce Innovation, LLC.<\/span><\/em><\/p>\n\n\n\n

17. \u201cGetting information off the internet is like taking a drink from a firehose.\u201d \u2013 <\/span>Mitchell Kapor<\/span><\/a>, founder of Lotus Development Corporation and designer of Lotus 1-2-3, co-founder of the Electronic Frontier Foundation.<\/span><\/em><\/p>\n\n\n\n

18. \u201cOn average, people should be more skeptical when they see numbers. <\/span>They should be more willing to play around with the data themselves<\/span><\/a>.\u201d – <\/span>Nate Silver<\/span><\/a>, founder, and editor-in-chief of FiveThirtyEight.<\/span><\/em><\/p>\n\n\n\n

Data Quotes: Why Data Treatment Is Important<\/h2>\n\n\n\n
\"Data<\/figure>\n\n\n\n

Raw data doesn\u2019t provide companies with valuable insights. But data analysts<\/a> can manipulate it to access deep insights that lie within the data. As a result, how you treat your data can have a profound impact on the conclusions you make. These data quotes reaffirm the importance of managing data efficiently:<\/span><\/p>\n\n\n\n

19. \u201cData that is loved <\/span>tends to survive<\/span><\/a>.\u201d – <\/span>Kurt Bollacker<\/span><\/a>, computer scientist.<\/span><\/em><\/p>\n\n\n\n

20. \u201cI think you can have a ridiculously enormous and complex data set, <\/span>but if you have the right tools and methodology<\/span><\/a>, then it\u2019s not a problem.\u201d – <\/span>Aaron Koblin<\/span><\/a>, entrepreneur in data and digital technologies.<\/span><\/em><\/p>\n\n\n\n

21. \u201cIf somebody tortures the data enough (open or not), <\/span>it will confess anything<\/span><\/a>.\u201d – <\/span>Paolo Magrassi<\/span><\/a>, former vice president, research director, Gartner. <\/span><\/em><\/p>\n\n\n\n

22. \u201cIn the spirit of science, there really is no such thing as a \u2018<\/span>failed experiment<\/span><\/a>.\u2019 Any test that yields valid data is a valid test.\u201d –  <\/span>Adam Savage<\/span><\/a>, creator of MythBusters.<\/span><\/em><\/p>\n\n\n\n

23. \u201c<\/span>Data are just summaries of thousands of stories<\/span><\/a>\u2013tell a few of those stories to help make the data meaningful.\u201d – <\/span>Chip and Dan Heath<\/span><\/a>, authors of \u201cMade to Stick\u201d and \u201cSwitch.\u201d<\/span><\/em><\/p>\n\n\n\n

24. \u201cErrors using inadequate data are much less than those using no data at all.\u201d – <\/span>Charles Babbage<\/span><\/a>, mathematician, engineer, inventor, and philosopher.<\/span><\/em><\/p>\n\n\n\n

25. \u201cThe data fabric is the <\/span>next middleware<\/span><\/a>.\u201d – <\/span>Todd Papaioannou<\/span><\/a>, entrepreneur, investor, and mentor.<\/span><\/em><\/p>\n\n\n\n

Data Quotes: Data Privacy and Security<\/b><\/h2>\n\n\n\n
\"Data<\/figure>\n\n\n\n

The data collected by corporations and government agencies can be loaded with sensitive information. For example, it can contain personally identifiable information, corporate secrets, and more. When you\u2019re dealing with highly sensitive information, enhanced privacy and security will be vital to ensuring compliance. Here\u2019s what the experts have said about data privacy and security:<\/span><\/p>\n\n\n\n

26. \u201cEverything we do in the digital realm\u2014from surfing the web to sending an email to conducting a credit card transaction to, yes, making a phone call\u2014<\/span>creates a data trail<\/span><\/a>. And if that trail exists, chances are someone is using it\u2014or will be soon enough.\u201d – <\/span>Douglas Rushkoff<\/span><\/a>, author of \u201cThrowing Rocks at the Google Bus.\u201d<\/span><\/em><\/p>\n\n\n\n

27. \u201cBetter be despised for too anxious apprehensions than ruined by too confident security.\u201d – <\/span>Edmund Burke<\/span><\/a>, British philosopher and statesman. <\/span><\/em><\/p>\n\n\n\n

28. \u201cYou happily give Facebook terabytes of structured data about yourself, content with the implicit tradeoff that Facebook is going to give you a social service that makes your life better.\u201d – <\/span>John Battelle<\/em><\/span><\/a>, founder, <\/span>Wired magazine<\/span><\/a>.<\/span><\/em><\/p>\n\n\n\n

29. \u201cIn (the) digital era, <\/span>privacy must be a priority<\/span><\/a>. Is it just me, or is secret blanket surveillance obscenely outrageous?\u201d – Al Gore, former vice president of the United States.<\/em><\/span><\/p>\n\n\n\n

30. \u201cIt\u2019s so cheap to store all data. It\u2019s cheaper to keep it than to delete it. And that means people will change their behavior because they know anything they say online can be used against them in the future.\u201d- <\/span>Mikko Hypponen<\/span><\/a>, security and privacy expert.<\/span><\/em><\/p>\n\n\n\n

31. \u201cYou know something is wrong when the government declares opening someone else\u2019s mail is a felony, but <\/span>your internet activity is fair game for data collecting<\/span><\/a>.\u201d – <\/span>E.A. Bucchianeri<\/span><\/a>, author.<\/span><\/em><\/p>\n\n\n\n

32. \u201cThe price of freedom is eternal vigilance. Don\u2019t store unnecessary data, keep an eye on what\u2019s happening, and <\/span>don\u2019t take unnecessary risks<\/span><\/a>.\u201d – <\/span>Chris Bell<\/span><\/a>, former U.S. congressman.<\/span><\/em><\/p>\n\n\n\n

Data Quotes: The Future of Data<\/h2>\n\n\n\n
\"Data<\/figure>\n\n\n\n

As technology evolves and becomes cheaper, all aspects of our personal and professional lives have the potential to become data-driven<\/a>. It\u2019s already changed the way most businesses and governments think and operate. The following quotes reflect what the experts have said about the future of big data:<\/span><\/p>\n\n\n\n

33. \u201cI keep saying that the sexy job in the next 10 years will be statisticians, <\/span>and I\u2019m not kidding<\/span><\/a>.\u201d- <\/span>Hal Varian<\/span><\/a>, chief economist, Google.<\/span><\/em><\/p>\n\n\n\n

34. \u201cBig data will <\/span>replace the need for 80% of all doctors<\/span><\/a>.\u201d – <\/span>Vinod Khosla<\/span><\/a>, co-founder of Sun Microsystems and founder of Khosla Ventures. <\/span><\/em><\/p>\n\n\n\n

35. \u201cThere\u2019s a <\/span>digital revolution taking place<\/span><\/a> both in and out of government in favor of open-sourced data, innovation, and collaboration.\u201d- <\/span>Kathleen Sebelius<\/span><\/a>, former U.S. secretary of health and human services.<\/span><\/em><\/p>\n\n\n\n

36. \u201c<\/span>Autodidacts<\/span><\/a>\u2014the self-taught, un-credentialed, data-passionate people\u2014will come to play a significant role in many organizations\u2019 data science initiatives.\u201d – <\/span>Neil Raden<\/span><\/a>, founder, and principal analyst, Hired Brains Research.<\/span><\/em><\/p>\n\n\n\n

37. \u201cWe should teach the students, as well as executives, how to conduct experiments, how to examine data, and <\/span>how to use these tools to make better decisions<\/span><\/a>.\u201d- <\/span>Dan Ariely<\/em><\/span><\/a>, professor of psychology and behavioral economics at Duke University and a founding member of the Center for Advanced Hindsight.<\/span><\/em><\/p>\n\n\n\n

38. \u201cEvery company has big data in its future, and <\/span>every company will eventually be in the data business<\/span><\/a>.\u201d – <\/span>Thomas H. Davenport<\/span><\/a>, American academic and author specializing in analytics, business process innovation, and knowledge management.<\/span><\/em><\/p>\n\n\n\n

39. \u201cBig data will spell the death of customer segmentation and force the marketer to understand each customer as an individual within 18 months or <\/span>risk being left in the dust<\/span><\/a>.\u201d – <\/span>Virginia M. (Ginni) Rometty<\/span><\/a>, chairman, president,<\/span><\/em> and CEO of IBM.<\/span><\/em><\/p>\n\n\n\n

40. \u201cThe world is <\/span>one big data problem<\/span><\/a>.\u201d – <\/span>Andrew McAfee<\/em><\/span><\/a>, principal research scientist, MIT. <\/span><\/em><\/p>\n\n\n

Get To Know Other\tData Analytics Students<\/h4>
\"Maura<\/a>

Maura Fields<\/p>

Data Analyst at Northeastern University<\/p><\/div>

<\/div>

Read Story<\/a><\/p><\/div><\/div>

\"Rahil<\/a>

Rahil Jetly<\/p>

Sales Operations Manager at Springboard<\/p><\/div>

Read Story<\/a><\/p><\/div><\/div>

\"Jon<\/a>

Jon Shepard<\/p>

VP Of AI Research Strategy And Execution at J.P. Morgan<\/p><\/div>

Read Story<\/a><\/p><\/div><\/div><\/div><\/div>\n\n\n\n

Parting Thoughts<\/h2>\n\n\n\n

According to MIT\u2019s Andrew McAfee, academia is failing to produce enough data scientists to meet present and future demands effectively. This has created a situation where companies tend to rely on what he calls \u201cHiPPOs\u201d or the Highest Paid Person\u2019s Opinion when forming their business strategies. <\/span><\/p>\n\n\n\n

In this scenario, deep insights will be presented to the leader, but this individual will still make a decision based on a gut feeling and not the data. So until we fill the talent gaps and change this (broken) approach, the world will continue to be \u201cone big data problem.\u201d<\/span><\/p>\n\n\n\n

If you\u2019re wondering if a <\/span>career in data science<\/span><\/a> is right for you, consider this final quote:<\/span><\/p>\n\n\n\n

41. \u201cPossessed is probably the right word. I often tell people, I don\u2019t want to necessarily be a data scientist. You just kind of are a data scientist. You just can\u2019t help but look at that data set and go, I feel like I need to look deeper. <\/span>I feel like that\u2019s not the right fit<\/span><\/a>.\u201d – <\/span>Jennifer Shin<\/span><\/a>, <\/span>data science\/machine learning\/AI expert and founder of 8 Path Solutions.<\/span><\/em><\/p>\n\n\n\n

Have we missed any of your favorite quotes about data? Or do you have any thoughts on the data quotes above? Tweet us<\/a>!<\/p>\n\n\n\n

(This post was originally published May 20, 2016. It was last updated June 14, 2019.)<\/em><\/p>\n\n\n\n

Since you\u2019re here\u2026
<\/strong>Interested in a career in data analytics? You will be after scanning this data analytics salary guide<\/a>. When you\u2019re serious about getting a job, look into our 40-hour Intro to Data Analytics Course<\/a> for total beginners, or our mentor-led Data Analytics Bootcamp<\/a>.\u00a0\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"

The amount of data generated in real time is immense. This has created oceans of data from which companies can derive real business value and make better business decisions. The big data market is predicted to grow by 20% this year, and by 2020, every human is expected to generate 1.7 megabytes (of data) every […]<\/p>\n","protected":false},"author":48,"featured_media":9437,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_eb_attr":"","_eb_data_table":"","footnotes":""},"categories":[134],"tags":[],"marketing_tags":[],"class_list":{"0":"post-1789","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-data-analytics"},"acf":[],"_links":{"self":[{"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/posts\/1789"}],"collection":[{"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/users\/48"}],"replies":[{"embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/comments?post=1789"}],"version-history":[{"count":3,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/posts\/1789\/revisions"}],"predecessor-version":[{"id":47743,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/posts\/1789\/revisions\/47743"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/media\/9437"}],"wp:attachment":[{"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/media?parent=1789"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/categories?post=1789"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/tags?post=1789"},{"taxonomy":"marketing_tags","embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/marketing_tags?post=1789"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}