10 Big data experts who deserve to be focused on Twitter

On the face of it, looking for the wisdom of big data on Twitter seems like an ironic suggestion. In fact, most ordinary consumers and business users use Twitter as a platform for data generation, and the information provided will be used as a source of analysis rather than as a guide to analyzing the solution.

Twitter does, however, carry a huge amount of valuable data expertise--provided we know where to find them. Like other social platforms, Twitter is sometimes as noisy as it has no real value. If you add the fashionable word "big data", the confusion and complexity will rise to new heights. So how exactly do we find valuable information that can be used for reference?

If you are not too entangled in the "big data" of this professional vocabulary, then the information found is often more reference. "Often, the most enthusiastic data-MongoDB are not" Big data experts, "says Matt Asay, vice president of marketing, Business development and group strategy at the company.

Asay and other experts who have insights into the big data field have brought us the most noteworthy publications on Twitter, and the news, advocacy, and networking of the publishers are enough to enrich the brains of the learners. Of course, we've also made a second round of selection, and finally made 10 big data experts on Twitter that deserve the most attention. Of course this is just a starting point--you can simply list yourself a longer list of concerns (which we will elaborate later). When it comes to the common features of their list of recommendations, these experts have successfully completed the difficult task of disseminating large data knowledge under the strict 140-letter limit.

This is certainly a good thing. Anyone can easily add "big data" or other relevant technical terms to their tweets or other means of communication, but that doesn't mean that these guys can really afford to be "expert"--just as I could discuss the recipe for a tasty pastry in a tweet, but that doesn't make me a great chef. So even talking about other technical areas, such as open source, outside the relevant terminology, while the apparent convergence of large data is not very close, it is equally possible to maintain a high degree of relevance. Please keep this premise in mind when choosing the object of attention, otherwise it is likely to be disturbed by the contents of the gaudy content.

Asay also pointed out that sometimes it is very effective to approach the source of specific information types. "I tend to be interested in Pew's study, which has direct access to important information, rather than being informed by other people," he said. ”

We have previously discussed such selection criteria in the article "Twitter's noteworthy IT leaders", which are naturally applicable in large data areas, but need to be adjusted in detail. We do not use a specific job rank or post as a criterion, as long as the content of the work is related to the clearance. (Here we only consider the individuals, organizations or businesses that publish information that are not within the scope of consideration.) )

We also have to do with publishers who are involved in sales, marketing, and other similar issues with large data solutions. Asay himself is a good example-although his release is equally noteworthy, he has an important position in "marketing, business development and corporate strategy", so we will not include him in the list. We have no hard demands on the number of existing followers to focus on, after all, what is more important is the quality and consistency of the information released, rather than the level of popularity (though there are indeed a number of people on this list who already have a lot of attention).

Let's go back to the list itself: what are some of the ideal concerns that this choice missed? We think the list itself is very good, but it is only a beginning rather than a final result. Depending on your personal orientation, you can also have a different personal choice. Why do we have to cling to the shackles of circles, learning and existing networks? The essence of social platforms is to share, so don't be hindered by too many unnecessary factors. You may want to write down your favorite big data technology gurus in the comments so that their insights can inspire more people.

Gartner it analyst, Merv Adrian (@merv)

MongoDB's Asay recommend Adrian, in addition to Gartner's colleague Svetlana Sicular and RedMonk, Stephen O ' Grady (also ranked on this list) has been affirmed. Asay said the few were good partners to help him understand the big data. One reason: Three people never engage in hype or gimmicks. "Each one can help us to sketch out the Big Data macro framework more clearly without being overwhelmed by the endless stream of hot news," Asay points out. Adrian's tweets are often dominated by Hadoop, NoSQL, and Microsoft.

RedMonk Company analyst Stephen O ' Grady (@sogrady)

O ' Grady is another of the big Three that Asay recommends, and it's easy to miss a friend who looks for it directly by searching for hot words--"big data". His tweets and blogs involve a variety of software and development topics, and are not limited to this. Here's a reminder to the Yankees fans: O ' Grady is a New England person, so sometimes there's news about the Red Sox-and it's often related to it technology.

Gartner Research director Svetlana Sicular (@Sve_Sic)

As the third largest data Asay recommended, Sicular's tweets revolve around Big data, analytics, business intelligence, data warehousing, data architecture, and Hadoop. She also mentions specific vendors in large data areas, such as Cloudera, and shares the reports she has learned in her Gartner research, for example: by 2015, 25% of large enterprises will be staffed with "Chief data officer" positions.

Kirk Borne, professor of data scientists, astrophysics and Computer Science, George Mason University (@KirkDBorne)

Don't be intimidated by the term "rocket scientist", borne often makes some suggestions on Twitter, and regularly brings us news and links related to big data and related topics. In the view of MongoDB's Asay, Borne's tweets are equivalent to an industry-readable list-a claim that has been widely accepted by technicians. Borne "regularly publishes and forwards links to articles that are closely related to large data and data science," said David Smith, CEO of Revolution Analytics. "I like to see him take a scientific view of such traditional, business-oriented articles. ”

Kdnuggets.com website Editor Gregory Piatetsky (@kdnuggets)

Piatetsky's Kdnuggets website, where KD refers to ' knowledge Discovery ', is a treasure trove of large data, data mining and analysis information. Besides focusing on the above points, his tweets often involve various kinds of large data guidance messages circulated on the Internet. Please pay special attention to your job seekers: The Kdnuggets website also regularly publishes the latest information related to data technology jobs.

Data scientist and journalist Lillian Pierson (@BigDataGal)

Is there any reason why we should not express our love for an employee who is a data scientist and journalist with two pairs of identities? Pierson through his own Data-mania website with a number of customers to maintain close cooperation, her tweets bring a large number of large data-related news, data visualization discussion, data-related vendors and other topics.

Analytical-solution Company founder Carla Gentry (@data_nerd)

As a professional data scientist, gentry the news and trends in his own sharp perspective, and in the tweets, analyzes these factors that may affect the direction of business. She is often able to come up with her own judgments, for example, data science is not synonymous with big data--in fact, the former appears much earlier than the latter.

Fitzgerald company founder and President Jaime Fitzgerald (@jaimefitzgerald)

Fitzgerald is working closely with Wall Street banks and other companies to jointly develop quantitative and data-driven business development strategies. His tweets focused on analysis, the impact of large data on benchmark performance, major business activities, data science, and other issues.

Ovum Company IT analyst Tony Baer (@TonyBaer)

As a highly praised practitioner in the industry, Baer is leading a large data research effort at Ovum. He often mentions a series of large data topics in tweets, including Open data and data management; Cloudera, MongoDB, Cloudant and Hortonworks and other related companies and platforms, plus other related topics. He has worked in journalism in his previous career and has served in a number of knowledge companies, including InformationWeek.

Spark Strategic Business Solutions company CTO Marcus Borba (@marcusborba)

If you are interested in how to translate large data into real business performance--in other words, into money--then Borba tweets can never be missed. In addition to regularly releasing tweets related to large data and analysis transactions, Borba also shares ideas and suggestions from other interested audiences.