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Top 31+ data and analytics conferences to attend in 2017

Don't miss the best big data and analytics conferences this year

2017 is shaping up to be a banner year for big data and analytics conferences. Whether you’re a data scientist, IT manager, architect, analyst, or chief data officer, there are all kinds of conferences to choose from. They range from small gatherings focused on research and industry trends to gigantic conferences that attract thousands of attendees and include major product announcements and research findings.

The list below highlights over two dozen events, sorted into four categories

  • Must-attend conferences - events with top-notch reputations, A-list speakers, and solid networking and workshop opportunities
  • Worth attending - this list includes niche events that appeal to a more focused audience
  • Other conferences of note - includes smaller symposia, regional events, and up-and-coming conferences

After reading the brief summaries below, be sure to click through to the conference websites to see more information, including conference schedules, speaker lists, and accommodation options.  

Must attend data and analytics conferences

KDD 2017

  • Twitter: @kdd_news / #KDD2017
  • Web:
  • Date: August 13-17, 2017
  • Location: Halifax, Nova Scotia
  • Cost: (Full conference) $1,090 for SIGKIDD/ACM/AAAI/SIGMOD members; $1,215 for non-members; $590 for students and (one-day passes) $490 for all registration types

This is a long-standing event put on by the The Association for Computing Machinery's Special Interest Group on Knowledge Discovery and Data Mining. KDD is focused on science and engineering topics, and brings together researchers and practitioners from data science, data mining, machine learning, knowledge discovery, large-scale data analytics, and big data. Industry is heavily represented, but this gives attendees a chance to speak to researchers working at some of the top companies in the field.

There are a lot of sessions to choose from, many of them focused on new applications as opposed to basic methodology, said Yisong Yue, an assistant professor at Caltech. Sometimes the choices can be overwhelming. "Sunday was the workshop day, and again, it made me wish I could split myself to cover many in parallel, with topics like large-scale sports analytics, learning from time series, deep learning from data mining, and stream mining," said Theodore Vasiloudis, a researcher at the Swedish Institute for Computer Science who attended KDD 2016. "In the end, I chose to spend most of my day in the workshop on mining and learning from graphs, which was closest to my interests and probably the best of the day." 

Who should attend: Data scientists and engineers who seek exposure to cutting-edge research and industrial applications of machine learning. It is also for people interested in presentations by scientists and engineers working for some of the largest data-focused companies in the world, such as Amazon, Netflix, and Facebook.

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ICDM 2017

  • Twitter: #icdm2017
  • Date: November 18-21, 2017
  • Location: New Orleans, LA
  • Cost: (Early bird) $850 for IEEE members; $1,020 for non-members; $450-$550 for students and (regular registration) $1,020 for IEEE members; $1,220 for non-members; $540-$660 for students

Last year's event cost 850 euros for IEEE members and 1,000 euros for non-members, with discounts available for early registrants and students. The IEEE International Conference on Data Mining is a premier international conference that brings together academic researchers and data scientists working in industry to discuss cutting-edge data mining applications in various fields. For instance, at ICDM 2016 in Barcelona, there were workshops on data mining in energy modeling and optimization, security, IoT, and politics. Speakers include leading academic researchers as well as data scientists working on projects in various vertical markets. Sourav S. Bhowmick of Singapore's Nanyang Technological University was impressed by last year's presentations, calling attention to a keynote that discussed a big data project that wasn't successful. "When was the last time a keynote shared lessons from failure?" Bhowmick tweeted. 

Note that the IEEE ICDM event is not to be confused with the Industrial Conference on Data Mining taking place in New York July 12-16.

Who should attend: Senior data professionals and data scientists working for industry. Unlike other research-focused events, ICDM makes it possible to see how cutting-edge data mining techniques are applied to real-world problems.

Strata + Hadoop World

  • Twitter: @strataconf / #StrataHadoop
  • Web:
  • Date: July 12-15, 2017 (Beijing); September 25-28, 2017 (New York); December 4-7, 2017 (Singapore)
  • Cost: $1,595 to $2,395. Discounts are available to students, academics, government employees, and corporate teams.

The Strata + Hadoop World conference series put on by O'Reilly and Cloudera is considered a must-attend event among scientists, engineers, and senior data managers working in industry. Companies presenting at the San Jose event include LinkedIn, Amazon, Uber, and other big names in the industry, plus occasional special appearances—President Obama gave the video keynote in 2016. As you might expect, the tutorials are laser-focused on technologies and platforms including Hadoop, Spark, AWS, and more. Keynotes include real-world case studies from technology companies and other firms that deal with big data—think credit card companies and the like.

Noel Welsh of Underscore Consulting has participated in several Strata + Hadoop World events in recent years, and says the events have gotten bigger and more focused on how companies can create business value using big data. "Whilst there were plenty of talks about how companies are still building their data pipeline, it’s good to see that many are past that stage and now figuring out how to derive value from their data (which is a much more interesting problem to me)," he wrote. 

Who should attend: There is both a technical and strategic focus to Strata + Hadoop World, and to get the most out of the conference, a strong technology background is required.

[See also: Data Locality in Hadoop: Taking a Deep Dive]

TDWI Chicago and TDWI Leadership Summit

  • Twitter: @TDWI  /#TDWIChicago
  • Date: May 7-12, 2017
  • Location: Chicago, IL
  • Cost: $1,460 to $3,645

If you want to take data analytics to the next level at your organization, then you should probably be at TDWI's Chicago extravaganza. The Data Warehouse Institute was founded in the mid-1990s to provide vendor-neutral training and research. TDWI is synonymous with education targeting professionals responsible for analytics, business intelligence, data modeling, and related topics. Whether you are looking to obtain professional certifications or are interested in gleaning best practices to bring back to your organization, TDWI is the place to be.

Sessions are "taught by in-the-trenches practitioners who are well known in the industry," reported consultant Jim Harris. Another attendee said the amount of information attendees have to absorb can be exhausting, but at the end of each day, they are likely to be smiling from all of the great takeaways

Some sessions target relative newcomers ("Big Data Fundamentals") while others are intended for experienced professionals ("TDWI Data Visualization: Solving Complex Data Integration Challenges"). Still others serve as refreshers ("Data Discovery, Exploration, and More: The Latest Innovations in Analysis and BI Tools") or are more oriented toward "soft" topics such as leadership and ethics.   

Who should attend: Business and IT leaders, data analysts, data warehousing and data integration specialists, architects, designers, and developers.

NIPS 2017

The 31st Annual Conference on Neural Information Processing Systems (NIPS) is a big AI conference that keeps on getting bigger—it apparently sells out every time even though organizers have booked larger venues in recent years. The conference has a heavy-duty science and engineering focus, with talks, paper presentations, and workshops on topics such as neural networks, deep learning, and clustering. Attendees view the conference as "intellectually stimulating," and one of last year's attendee—Stanford researcher Andreas Stuhlmüller—felt compelled to put together a top 50 list of the things he learned over the course of five days. "Why does deep learning work now, but not 20 years ago, even though many of the core ideas were there?" he said after seeing a presentation on neural nets. "In one sentence: We have more data, more compute, better software engineering, and a few algorithmic innovations."

Who should attend: Researchers, data scientists, and engineers seeking to grasp major trends in AI and machine learning, as well as those interested in hearing from some of the world's leading researchers from academia and industry. The 2016 event included Yann LeCun, a leading machine learning researcher who now heads Facebook's AI research team.

The Data Science Conference

  • Twitter: @_tdsc_ #tdsc
  • Web:
  • Date: April 20-21, 2017 (Chicago), September 21-22, 2017 (Seattle)
  • Location: Chicago, IL, and Seattle, WA
  • Cost: $1,200 for single pass and discount rates for groups, academia, government employees, and non-profit employees

TDSC is universally praised by attendees for being sponsor-free, vendor-free, and recruiter-free. "The conference was very well put together and had a good lineup of interesting and relevant speakers," wrote John Shrewsbury, Ph.D., after attending last year's event in Chicago. "It was great to interact with other practitioners from around the world and not have to worry about being overwhelmed by vendors contacting me upon my return home."

No sponsors, vendors, or recruiters is a rare trifecta in this day and age, but this freedom comes with a price: "The downside of this model is someone still has to pay the bills, and in this case it is the attendees," wrote Bob Gourley. "But the upside is an ability to focus like a laser beam on things that matter to the data science community."

Indeed, TDSC is friendly and fast-paced, with breakout sessions and a strong science focus. Sessions focus on data science in industry, with speakers hailing from Microsoft, Facebook, Allstate, Amazon, Verizon, GE, Google, Air Canada, and Children's Hospital of Orange County, among others.

Who should attend: People involved with data science, data mining, big data, machine learning, artificial intelligence, and predictive analytics.

O’Reilly Artificial Intelligence Conference

O’Reilly has a lot of experience developing top-notch tech conferences (see the Strata + Hadoop entry), and the O'Reilly AI Conference is no different. The focus is applied AI—how to implement AI, deep learning, and related technologies in real-world projects. The conference targets a technical audience, with dozens of breakout sessions organized by skill level. Last year's conference had a strong list of speakers, including deep learning research pioneer Yann LeCun, who now heads up Facebook's AI research arm, and Peter Norvig, Google's director of research. As you might expect, discussions of specific approaches to deep learning and AI figure prominently, although there is plenty of room for case studies and discussions of industry trends, along with warnings from speakers about the real challenges associated with leveraging emerging AI technologies. "Speakers reminded everyone about the recent successes of deep learning—self-driving cars, super-human image recognition, video captioning, AlphGo, etc.," wrote Howard Goldowsky, who attended the 2016 event. "But many focused their talks on how little insight we currently have about why it all works."

Dan Woods also noted some skepticism about what AI is capable of. "Gary Marcus of Geometric Intelligence spent his entire presentation explaining in great detail with excellent supporting evidence why we are a long way from anything resembling strong AI," he said. "His point essentially was that successes of current AI were very narrow and brittle. If you just change a few aspects of the problem being solved they utterly fail, especially at the infrequent long tail cases that are always part of real life."

Who should attend: Scientists and engineers responsible for data science, data mining, big data, machine learning, and AI at their respective organizations.

Big Data Innovation Summit

The Big Data Innovation Summit is an international series of events focused squarely on the needs of large organizations and their data management needs. Speakers this year hail from eBay, Huawei, Google, ESPN, and the California Department of Justice, showing how their respective teams use data to better understand customers, advance technology platforms, and drive innovation across the enterprise. Past summits have also included sessions that touch on soft topics such as ethics, privacy, and leadership. Alpesh Doshi, founder of U.K.-based Fintricity, indicated that the event offers a chance to discuss with peers issues ranging from finding talented people to advancing the digital transformation agenda at large companies. "I was surprised to find the mature companies were mostly still at early stages of applying big data technology," he remarked after attending last year's summit. "The digital transformation agenda was again still early and there was confusion around what a 21st century business should look like."

Note that there are several other Big Data Innovation summits this year, including Las Vegas in January, London in March, and Boston in the fall.

Who should attend: Senior IT managers from Fortune 500 companies and other large organizations, including government. It is also for IT professionals who are not only interested in learning how big data can help solve existing problems, but also want to explore how big data can be leveraged for new products and services.

Worth attending

WSDM 2017

WSDM is an academic-style conference with paper and poster presentations. Data scientists, students, and startups go to this conference for an in-depth look at various web search and data mining techniques, "with an emphasis on practical yet principled novel models, algorithm design and analysis, economic implications, and in-depth experimental analysis of accuracy and performance." Sessions include "Tutorial: Utilizing Knowledge Graphs in Text-centric Information Retrieval." Attendees of past WSDM conferences have been enthusiastic: "The conference itself was a single track mixture of mostly long, 20 minutes talks and few shorter talks," wrote researcher Mor Naaman after attending the 2014 conference in New York. "The sessions revolved around Web Search, Advertising, Recommender Systems, Network Analysis, Language Analysis and Crowdsourcing," he said.

Keynote speakers include leading scientists and researchers, but a heavy industry contingent will be there as participants or sponsors, including the usual suspects: Facebook, Google, Microsoft, etc.

Who should attend: Data scientists and people interested in new research about data mining, natural language processing, neural networks, and other topics.

Joint Statistical Meetings

  • Twitter: @AmstatNews / #JSM2017
  • Web:
  • Date: July 29-August 3, 2017
  • Location: Baltimore, MD
  • Cost: (Pre-June 29) $485 for members and $740 for non-members; (post-June 29) $535 for members and $815 for non-members; discount rates available for groups, academia, and one-day passes

This is one of the largest events on the list. It's the American Statistical Association's big annual show, with some 6,000 attendees coming to Baltimore to talk about stats, statistical tools and methods, and applications. Attendees have raved about past gatherings, with one attendee remarking that his Fitbit couldn't handle all of the activity. If you are interested in getting more details about what JSM events are like, check out data scientist David Robinson's play-by-play of both JSM and useR conferences. However, researcher Julien Cornebise warned that it's difficult to learn much from the short presentations and nonstop sessions taking place at the same time; rather, the big opportunity is in networking and maintaining industry connections. "Nowhere else can you meet all of your U.S.-based colleagues face to face at the same time in the same place, exchanging scientific ideas or just spending some great time in an informal context, getting to know each other better in a relaxed setting," Cornebise wrote. "JSM is like iterating the adjacency matrix of your graph by several steps: Not only do you strengthen your links with colleagues/friends you already know and appreciate, but you also get to know those they know, and find great matches!" However, he added that it can be difficult to leverage these opportunities if you don't have many connections: "I’d recommend going there with a few colleagues from your institution for the first time." 

Who should attend: Statisticians and data scientists.

useR! 2017

  • Twitter: @UseR_Brussels  / #useR2017
  • Date: July 4-7, 2017
  • Location: Brussels, Belgium
  • Cost: €375 to €650. Discounts available for students

useR! is a forum for the R user community, which is heavily weighted toward data scientists and statisticians. Keynotes include discussions of topics of general interest to statisticians as well as user presentations about practically any R-related topic. Keynotes this year will cover structural equation modeling, dose-response modeling in R, R programming, and teaching R. There is also a social program and poster sessions.

If last year's conference in Stanford is anything to go by, the conference is inclusive and wide-ranging in terms of topics covered. "The conference was highly attended, with around 900 registered delegates split 50:50 across academia and industry," reported Dr. Becca Wilson, a research fellow at the University of Bristol. She noted that 30 percent of the attendees were female, organizers supported researchers with disabilities, and the 2017 conference will have childcare for kids aged 2-14.

Who should attend: Statisticians and data scientists.

Enterprise Data World

EDW has been around for more than 20 years, and targets professionals who want to take their data projects to the next level. It's an international conference, with more than 1,000 attendees from dozens of countries. Speakers come from established online and traditional businesses, and are also independent experts and academics. There are lots of panels and discussions around policies, including ethical issues that pop up around the storage and use of data. "If you are collecting data, think about what would Dr. Evil do with it?" asked professor Karla Carter of Belleview University during one EDW 2016 session.

Who should attend: Mid-level and senior managers responsible for managing their organizations' data and setting policies around data, as well as professionals interested in practical issues such as records management and database technologies.


  • Twitter: @odsc / #ODSC
  • Web:
  • Date: May 3-5, 2017  
  • Location: Boston, MA
  • Cost: $499 to $1,699. Early discounts available prior to January 7.

Open Data Science Conference East is a big show, part of series that takes place in the U.S., Europe, and Asia. It has a near-cult following among attendees, many of whom return year after year to catch up with old friends and learn some new skills. Four tracks are listed: Open Data Science, Machine Learning, Big Data Science, and Open Visualization. Speakers come from industry and academia, and include luminaries such as Max Kuhn, one of the world's top R experts, as well as people with specialties in certain data sets (U.S. Census) and techniques (visualization).

ODSC East is aimed at in-the-trenches data science people and engineers, but it's also suitable for newcomers as well as people conducting career-related networking. "If you are new to data science or are just interested in learning more about data science, then ODSC is a really great venue to meet incredibly talented individuals as well as attend high-quality technical talks," said Charles Givre, a data scientist at Booz Allen Hamilton. He added that it's a great value, especially for people interested in training.

Who should attend: Engineers seeking to beef up their data science skills, students and professionals looking for jobs, and employers looking to hire.

The Machine Learning Conference

  • Twitter: @MLconf / #MLconfSF
  • Web:
  • Dates: September 15, 2017 (Atlanta, GA) and November 10, 2017 (San Francisco, CA)
  • Cost: $200

This is a daylong event targeting machine learning professionals in New York and Seattle. The price is low, but there is a lot of value for up-and-coming engineers and data scientists. Expect lots of solid presentations about machine learning tools used to solve real-world problems. One attendee praised the conference for a diversity of speakers and topics. Speakers include the usual suspects—Netflix, Google, Pinterest, etc.—but there are also opportunities to see other companies and vendors. Here's a list of the 10 main takeaways from last year.

Who should attend: Mid-level scientists and engineers in New York and Seattle.

Big Data Analytics, Tokyo

Big Data Tokyo is a new conference organized by Basis Technology (which in the past has hosted conferences on search-based applications in Tokyo) and Open Data Science, the organizer of the ODSC family of conferences, including ODSC East, mentioned earlier. The event is business-focused, although many speakers and attendees hail from smaller companies on the bleeding edge. Organizers list "deriving business value from data science" as a prime focus, and promise to "showcase compelling applications of big data analytics and data science to the business world, and to help our audience identify and appreciate true innovation as distinct from the marketing hype."

Presentations will be in both English and Japanese, with simultaneous interpretation and bilingual slides available for all keynote presentations. The "father of glanceable technology" and @DittoLabs founder David Rose will be keynoting this year, discussing how companies can profit from the Internet of Things. Other talks include practical machine learning using IoT data, data science at a fintech company, and a behind-the-scenes peek at a Japanese analytics startup.

Who should attend: Aimed at both "geeks" and "suits," according to conference organizers, with technical ideas being presented in a way that a general business audience can appreciate.

Global Artificial Intelligence Conference and Big Data Bootcamp

Like many other big data and AI events, the Big Data Bootcamp and Global Artificial Intelligence Conference has grown in size in recent years. Approximately 1,000 attendees will pile into the Santa Clara Convention Center to talk AI from January 19-21, while the Big Data Bootcamp will be overlapping from January 20-22.

The AI conference is industry-focused as opposed to research-focused, with speakers from big companies such as Intuit, Microsoft, Yahoo, Google, Amazon, and Apple. One of the most interesting keynotes will feature Amazon AI researcher Ashwin Ram talking about conversational AI with Alexa, the AI used in the Amazon Echo. Lots of case studies will be presented, ranging from natural-language processing in the pharmaceutical supply chain to how to become a self-driving car engineer.

The Big Data Bootcamp is a fast-paced technical overview of the big data landscape, focusing on "Hadoop, Spark, NoSQL, data science, machine learning, artificial intelligence, and deep learning." Organizers claim no technical experience is required, but they promise to give a boot camp-style experience, cramming a month's worth of use cases and training into three eight-hour sessions. If you manage to survive all three days, you will get a big data certification. Organizers say both events are vendor-agnostic.

Who should attend: Global Artificial Intelligence Conference: IT managers, executives, and engineers responsible for AI, innovation, and product development.
Big Data Bootcamp: Engineers, data scientists, statisticians, DBAs, analytics professionals, architects, networking specialists, managers, students, data analysts, QA staff, data warehouse professionals, sales staff, technical marketing staff, and project managers.

Chief Data Officer Summit

This is another event put on by Innovation Enterprise, which also organizes the Business Analytics Innovation conference mentioned earlier. The speaker lineup is one of the most impressive we've seen, featuring CDOs and top-level data scientists from PayPal, HSBC, IBM, Bing, World Bank, Visa, LinkedIn, Shell, TD Bank, Los Angeles County, and Sony Pictures, just to name a few. Allison Sagraves, a speaker and CDO who participated in last year's event, was impressed by the presentation on the industrial Internet. There was also a lot of buzz about data quality and the classic "garbage in, garbage out" challenge, with attendee Anthony Juliano quipping that "'Data Janitor' is the next major role." 

Who should attend: Aimed squarely at CDOs, but up-and-comers in BI and analytics will find value as well. A number of industries are represented, but finance and banking dominate the speaker list.

Predictive Analytics World

  • Twitter: @pawcon / #pawcon
  • Web:
  • Dates and locations: February 2-3, 2017 (Dusseldorf, Germany), May 14-18, 2017 (San Francisco, CA), June 19-22, 2017 (Chicago, IL), October 11-12, 2017 (London), October 29–November 2, 2017 (New York, NY), November 13-14, 2017 (Berlin, Germany) 
  • Cost: Varies by location (for instance, $3,495 to $4,000 in New York). Early discounts available.

The PAWCon travelling roadshow hits locations in the U.S. and Europe in the first half of this year, with each event including sessions for specific verticals. For instance, Dusseldorf includes a manufacturing track, while San Francisco includes workforce-related sessions. While there is a strong business focus at all of the events, workshops allow attendees to roll up their sleeves and dive into technologies with sessions like Hadoop for predictive analytics, R boot camp, and R for predictive modeling. Keynotes include industry best practices and vendor talks.

"I really enjoyed the conference because of the fact that most of the attendees were trying to bridge the roles of technology and analytics with business insights through predictive modelling, and most of the speakers made a point of speaking about the ways to use data to leverage business insights," wrote WiseAnalytics President Lyndsay Wise after attending PAWCon in 2013. "Much of the discussion surrounded 'big data' and how to leverage analytics within environments that contain large, complex, and real-time related data."

Who should attend: IT and business managers responsible for analytics, data, and strategy.

MIT Chief Data Officer and Information Quality Symposium

The 11th annual MITCDOIQ (yes, that's the official acronym) takes place on the campus of the MIT Sloan School of Management and is focused on the professional development of chief data officers. Sessions deal with not only the traditional responsibilities of CDOs, but also emphasize their roles in enabling business, collaboration, and innovation across the organization. Past sessions have explored how CDOs connect the dots between data management and marketing and the evolving role of the CDO in life sciences and healthcare. 

The event has been well-received in the past. Big data authority KDnuggets praised it for being "well organized" and an "excellent program," but not everyone drinks the CDO Kool-Aid. One consultant decried the event as a "CDO Love-fest" with the role of CDO little more than a "fashion statement" by organizations that want to be perceived as big data innovators.

Who should attend: Chief digital officers, analysts, and business execs.

Data Summit 2017

Organized by Database Trends and Applications and Big Data Quarterly, the annual summit features workshops, conference tracks, a two-day security forum, and a popular Readers' Choice award program. The focus is on high-level topics of interest to C-level IT managers and their senior engineering staff. For instance, last year's summit featured topics such as "Data Engineering for the Internet of Things," "Moving from Traditional BI to Data Discovery," and "Making the Shift from Relational to NoSQL."      

Who should attend: Aimed at C-level people plus analysts, scientists, and business execs in industry and government.

Leverage Big Data '17

This is a well-regarded event organized by big data news portal Datanami, event organizer nGage, and Tabor Communications. Expect lots of sessions exploring industry trends ("Big Data, Digital Transformation and the Second Machine Age"), as well as keynote case studies presented by IT leaders from Netflix, Thomson Reuters, and others. There will also be panels to discuss strategies for big data and storage, as well as shorter case studies presented by vendors and their clients. Check out an account of one of the keynotes at a recent Leverage Big Data conference ("many excellent ideas and insights about the current state of big data") as well as a Datanami article about last year's conference

Who should attend: Senior business and IT leaders responsible for big data and storage.

Other conferences of note

Business Analytics Innovation

Business Analytics Innovation is a relatively small conference, with approximately 150 attendees gathering in Las Vegas to hear presentations and case studies with a focus on business analytics, BI, and big data. The speakers represent tech companies as well as consumer-focused companies that use analytics on a massive scale. For instance, an executive from MasterCard will be discussing how big data is helping the company drive rewards and loyalty, while a data scientist from Zappos will address A/B testing, and a director from MGM Resorts International will discuss pricing analytics. Other presenters include executives, product managers, and data scientists from Airbnb, Google, EA, and Equifax, among others.

Who should attend: IT managers, product managers, data scientists, and analytics professionals.

Chief Data and Analytics Officer

The InterContinental Miami in January sure sounds nice, and the Chief Data and Analytics Officer conference makes it even better with a solid speaker lineup. Capital One's CDO kicks things off with a presentation on using analytics to maintain a competitive edge, and evaluating new data sets for your company. Later in the morning, a panel of CDAOs looks at proving value for your organization and how to garner new insights from new data sources, experiences, and AI. Additional presentations and panels look at data governance, innovation, deep learning, and fostering a data-driven culture. While there is not a specific vertical focus, the banking and finance industry is heavily represented in the speaker lineup.

The conference is small (100-plus attendees), but that makes it much easier to network with attendees and speakers. The event organizer is Corinium Global Intelligence, which specializes in data- and analytics-focused events across the world.

Who should attend: C-suite executives responsible for data and analytics.

IDC Big Data and Analytics Conference

This is a smaller conference that takes place in various international locations. For this year's event in London, registration is free as long as you are not a vendor, but accommodations are not included.

The conference is heavy on industry trends that firms in Europe can leverage as they develop big data/analytical strategies. One attendee at the 2013 conference in Sydney noted, "although the standard of presentation was high, I couldn’t help but hear fellow attendees comment about the lack of practical examples, particularly in the field of predictive analytics." However, the agenda now includes several panels that allow attendees to ask questions of the keynote presenters and executives to understand how they overcome specific issues within their organizations. In the afternoon there will also be peer-to-peer discussion groups around issues such as transitioning to the cloud, monetizing data assets, and analytic architectures.  

Who should attend: Senior analytics/BI directors, and IT managers responsible for data, architecture, and product.

Big Data & Analytics Innovation Summit Singapore

Yet another Innovation Enterprise event but this time located in Asia. For the fifth annual Singapore gathering, there will be more than 35 speakers, including CIOs, CDOs, COOs, and heads of data initiatives at companies including Merck, Uber, Allianz, Spotify, Johnson & Johnson, BP, Rolls-Royce, and several Singaporean governmental bodies. The focus is big data and analytics strategy and implementation, with lots of examples and case studies from speakers. Sample sessions this year include "The Role of Big Data in Robotics Process Automation," "Building Enterprise Data Strategy to Support Business Success," and a data architecture workshop led by Uber's chief data architect.

Who should attend: Leaders and data scientists responsible for analytics and data management, as well as officers focused on product and innovation.

Chief Analytics Officer Spring

If you miss Corinium's Miami event, mentioned earlier, there is a sister event held in Arizona in early May. It's a small event (approximately 100 attendees, Corinium says) focused on chief analytics officers. Speakers come from retail, media, gaming, insurance industry, and the chemical industry. Presentations and special sessions include "Building an innovative analytics organization," "Driving company-wide innovation from within the analytics team," and "Diversity in data and analytics." Interestingly, the format not only involves speakers lecturing from a podium, but also includes special peer sessions in which conference co-chairs and keynote speakers split the attendees into separate groups, which then have discussions about the analytics-related issues that matter most to them.  

Who should attend: Chief analytics officers and senior-level data managers.

Big Data Summit Canada  

The summit in Toronto has a solid speaker lineup from across North American industry. The keynotes and panels look at the big data and analytics landscape from 10,000 feet, but they get more into details when specific case studies are discussed. For instance, Dell, IBM, and HP will be giving talks on technology platforms and how to use analytics and big data to improve decision-making, while senior executives from The Weather Channel, Essex Power, and the Canadian Ministry of Finance will reveal how their organizations leverage data to achieve specific goals and outcomes.  

There are also optional workshops after the conference concludes: "Building an Advanced Analytics Team to Achieve Results" and "Planning Your Hadoop Transition to Minimize Interruptions."

Who should attend: Senior IT managers responsible for big data or analytics, and chief analytics officers.

Data Science Conference 2017

Targeting businesses, government agencies, and startups in India, Data Science Conference 2017 is an eclectic conference covering big data, analytics, AI, IoT, and security. In addition to keynotes featuring speakers from Vodafone, Barclays, and other corporate entities, there will also be heavy-hitters from governmental or quasi-governmental organizations, including the Department of Science & Technology and the Reserve Bank Of India.

Who should attend: IT managers and data scientists.

Machine Intelligence Summit  

This event is one of a series of global summits put on by RE.WORK that explores the connections between machine learning and AI. The San Francisco summit is small (about 300 attendees) and held in conjunction with the Machine Intelligence In Autonomous Vehicles Summit. There is a really interesting speaker list, including people from Amazon who lead development on the AI used in the Amazon Echo. Other speakers hail from Ancestry, Kohl's, Flickr, as well as the University of Montreal and other research institutions driving research into machine learning and AI.

Who should attend: IT and business managers, data scientists, and researchers.

Gartner Data & Analytics Summit  

Gartner's Data & Analytics Summit comes to the Dallas area in March. This a big event, with dozens of keynotes and special sessions dominated by topics related to leadership, strategy, and governance. There are also a fair number of discussions around industry verticals such as banking, healthcare, insurance, manufacturing, and government. Interestingly, several sessions about AI and machine learning have been added ("Tutorial: Understanding Artificial Intelligence in a No-Hype Zone"), as well as an appearance by Sam Esmail, the creator of Mr. Robot! Of course, one of the big draws of a Gartner event is hearing from Gartner analysts about looming trends, best practices, and Magic Quadrants to take back to your organization.

Who should attend: Chief data officers at large organizations, people responsible for data and analytics, and aspiring IT leaders.

Image source: Flickr

This article/content was written by the individual writer identified and does not necessarily reflect the view of Hewlett Packard Enterprise Company.