The Big Data technology and services market is one of the fastest growing, multi-billion dollar industries in the world. This market is expected to grow at a 26.4% compound annual growth rate to $41.5 billion through to 2018. Big Data has already become an essential part of our everyday lives. The collection, storage and analysis of enormous amounts of data allows us to track all of our online activity, look up and store our bank statements, shop efficiently, or engage in social media. Big data is also being used by companies to improve customer service, monitor the condition of individuals cars, or contribute to economic development. It has significantly enhanced our day to day lives and this trend will only continue as the capabilities of big data grows in the coming years.
Companies see big data as a new method of gaining an edge in the market. It is an incredibly effective tool for answering questions such as; how does a certain consumer group behave? How much should a company charge to maximise revenues? Answering these questions effectively will impact the business strategies of companies in every sector. Big data demands highly skilled professionals to identify the correct data to collect, manage big data sets and effectively extract conclusions that can be then applied within an industry.
WHAT ARE THE EXPERTS SAYING?
We reached out to some of the top 20 influencers to ask them for their views on Big Data. We spoke to Kirk Borne (#1), Ronald van Loon (#3), Gregory Piatetsky, KDnuggets (#4), Evan Sinar (5#), Bob E. Hayes, PhD (#7), Bill Franks (#8), Mark van Rijmenam (#9), Richard Brueckner (#11) and Prof. Dr. Diego Kuonen (#12). Be sure to follow them to stay up to date on the best content and resources on Big Data!
“Big Data has moved beyond its original hype phase, and even beyond its concept phase, and is now entering the productization and monetization phase. Every organization that is collecting vast sums of data now see that as an asset to generate better outcomes: new discoveries, improved decisions, and innovative products.”
“Data and data science have a massive influence on everything we do. Anything can generate data; from any devices to any online touch points. The impact that data has and will have on customer experience, business models and industries is tremendous and continues to grow every day. As a result, many companies are searching for the best way to create sustainable success from data. This all starts with customer-centricity and relevance. Companies want get to grips with customer journeys and know their customers on an individual level to establish a long-term relationship. But to do so, you need to create a fundament of structured and unstructured data from all relevant touchpoints through excellent data process management. With that in place, the right balance of data science and customer experience expertise can prescribe relevant actions and optimize users’ experiences, increasing their loyalty towards the brand. And that is exactly when sustainable value is created: when a company quits the narrow path to purchase and starts following the path to relationship.”
“Among the newest domains for Big Data’s immense reach – and risks – is the workplace, as a source of unprecedented data about employees. Increasingly, companies are using wearables, biometric sensors, and other devices to track and improve employee productivity. While these productivity gains can indeed be massive, alongside new workforce data come major quandaries for how it’s used to decide which employees get hired, promoted, and disciplined. If poorly-executed and viewed suspiciously, Big workforce Data will generate rampant employee resentment, disengagement, and turnover. Companies need their leaders to be both data-savvy enough to verify that all information gathered about employees is accurate and fair, and trusted enough to credibly communicate the rationale for capturing the data in the first place.”
“Big Data, GPUs, and better algorithms will make 2016 a breakout year for Deep Learning, which will achieve human or superhuman performance in many areas, with a focus on speech, image, and video recognition and analysis.”
“In our world of Big Data, businesses are relying on data scientists to glean insight from their large, ever-expanding, diverse set of data. Our research at AnalyticsWeek shows that, while many people think of data science as a profession, it’s better to think of data science as a way of thinking, a way to extract insights using the scientific method. The data science way of thinking requires three different types of skills: 1) subject matter expertise, 2) technology/programming and 3) statistics/math. Subject matter expertise ensures you are asking the right questions, generating and testing the right hypotheses. Technology/programming skills allows you to access / acquire / manage the data to address those questions. Finally, statistics/math skills are required to interrogate the data to answer your initial questions. When you look at data science as an approach, it’s easier to get your head around why a team of different types of data scientists is a good approach to tackling your Big Data problems. No one data scientist is an expert in all three skill areas. Instead, to get insight from your data, you are better off using a team of data professionals who have complementary data science skills. Businesses who have the right mix of data professionals on their team will be better equipped to outmaneuver the competition.”
“Big data continues to have an impact across the business world as organizations determine how to best analyze and act upon it. This trend will certainly continue just as the trend toward more analytics has been a steady one for many years. While big data adds a lot of new information to the mix, the underlying value is still about the insights and actions that can be derived through the analysis of big data.”
“Many believe that Big Data is over-hyped, but seeing the fantastic use cases popping up around the globe I would say Big Data is under-hyped! In the coming years, Big Data will revolutionize every industry unlike we have seen before!”
“When I first started writing about Big Data some five years ago, I thought it was about the search for a needle in a haystack. Now it’s clear to me that breakthrough analytic discoveries often have little to do with what you thought you were looking for.”
“Despite an awful lot of marketing hype, big data are here to stay and big data analytics (i.e. data science and statistics) will remain aids to human thinking and not replacements for it! As such, to ensure successful big data analytics outcomes do not neglect the following four principles: use sequential approaches to problem solving and continuous improvement; have a strategy for the project and for the conduct of analytics; carefully consider data quality and how data will be analysed (“data pedigree”); and apply sound subject matter knowledge, which should be used to help define the problem, to assess the data pedigree, to guide analytics, and to interpret and communicate the results.”
MAPPING THE COMMUNITY
We were very interested in seeing which Big Data professionals and brands were leading the online discussion, so we analysed 932K+ tweets from November 28th 2015 to January 26th, 2016 mentioning the keyword: #BigData. We then identified the top 100 most influential brands and individuals leading the discussion on Twitter. What we discovered was a very engaged community, with much discussion between individuals and brands. Below you can see a network map of the online conversation created with our Influencer Relationship Management software (IRM). Be sure to click on the map to enjoy the full size network diagram in greater detail.
Below you can see another network map created with our Influencer Relationship Management software (IRM) showing the #3 Brand Information Week at the centre, and the conversations to and from the different influencers in his field. If you are interested in learning more about identifying, managing and engaging with influencers click here to get in touch!
TOP 100 INDIVIDUALS
We looked at all the individuals engaging on Twitter to bring you a list of the top 100 most influential individuals in the Big Data landscape.
|Rank||Twitter Handle||Name||Company||Influencer Score|
|1||@KirkDBorne||Kirk Borne||Booz Allen Hamilton||100|
|2||@craigbrownphd||Craig Brown, Ph.D.||Consultant||86.15|
|3||@Ronald_vanLoon||Ronald van Loon||Adversitement||31.46|
|5||@EvanSinar||Evan Sinar||Development Dimensions International||23.57|
|6||@JimHarris||Jim Harris||Strategic Advantage||22.82|
|7||@bobehayes||Bob E. Hayes, PhD||AnalyticsWeek||22.57|
|8||@billfranksga||Bill Franks||Analytics Consulting||14.35|
|9||@VanRijmenam||Mark van Rijmenam||Datafloq||12.67|
|11||@insideBigData||Richard Brueckner||insideHPC Media||10.75|
|12||@DiegoKuonen||Dr. Diego Kuonen||Statoo Consulting||10.58|
|14||@robertoglezcano||Roberto A. González||San Pablo University||8.95|
|16||@dr_morton||Morten Middelfart||Genomic Expression Inc||8.18|
|17||@jladley||John Ladley||First San Francisco Partners||7.34|
|24||@Dana_Gardner||Dana Gardner||Interarbor Solutions||4.41|
|25||@jose_garde||Jose Javier Garde||Freelance||4.26|
|26||@Primary_Immune1||Yoni Maisel – CVID||Freelance||4.05|
|27||@TheRecordsGuru||Robin Woolen, IGP||The Records Guru||4.03|
|28||@OxygenMat||Muhammed Abdullahi T||Naija Writers’ Coach||3.97|
|29||@tedcoine||Ted Coiné||The Extraordinary Influencer Network||3.95|
|30||@bigdata||Ben Lorica||O’Reilly Media||3.77|
|31||@MarshaCollier||Marsha Collier||John Wiley and Sons||3.67|
|32||@mikepluta||Mike Pluta||DST Systems, Inc||3.54|
|33||@BigDataGal||Lillian Pierson, PE||Data-Mania||3.41|
|35||@jessicadavis||Jessica Davis||Information Week||3.34|
|40||@DBaker007||Duane Baker||Duane Baker||3.05|
|41||@RussWalker1492||Russell Walker||Kellogg School of Management||2.98|
|43||@kevinttully||Kevin Thomas Tully||Markistry & ScealCom||2.87|
|44||@NeilCattermull||Neil Cattermull||Compare the Cloud||2.85|
|45||@dez_blanchfield||Dez Blanchfield||The Bloor Group||2.81|
TOP 100 BRANDS
In the top 100 brands we can find a great selection of agencies and industry resources like Information Week and Datafloq, as well heavyweights such as IBM and Oracle.
|Rank||Twitter Handle||Name||Influencer Score|
|7||@techreview||MIT Tech Review||12.25|
|21||@DataScienceCtrl||Data Science Central||8.21|
|23||@TCS_Digital||TCS Digital Software||8.1|
|29||@IBMbigdata||IBM Big Data||6.92|
|31||@BigDataCareers||Big Data Careers||6.73|
|32||@BIG_DATA_News||Big Data News||6.49|
|37||@analyticbridge||Big Data Science||5.64|
At Onalytica we love building these lists and want to give back to our loyal readers as much as we can. If you’re interested in other topics (such as Machine to Machine, Wearable Tech, Internet of Things) be sure to have a gander on our blog or why not propose some topics to us on twitter? We also build some very cool software to manage all of these influencers. Get a free demo today by clicking the button below!
Disclaimer: As ever with these lists, it must be stressed that the ranking is by no means a definitive measurement of influence, as there is no such thing. The brands and individuals listed are undoubtedly influential when it comes to driving discussion in the Big Data debate.
The PageRank based methodology we use to extract influencers on a particular topic takes into account the number and quality of contextual references that a user receives. These calculations are independent of a user’s number of followers, but we do filter our lists based on how much a user is engaged in the conversation and the influence they drive through their networks.