Design, deliver, and run enterprise blockchain workloads quickly and easily.
All servers and systems
It's an exciting time to be part of the data and analytics world. Each day seems to introduce new technologies, with improvements for existing approaches and techniques. Businesses are recognizing the importance of making data-driven decisions—which means your boss is willing to invest in helping you learn about the field.
For anyone in the data and analytics community, it can be challenging to stay on top of all the changes, especially considering regular distractions at work. This is where data and analytics conferences come in. There's no better way to squeeze in everything you need to advance your career in analytics, learn new skills, and make new human connections.
To help you make the most of your time and money, we created a list of recommended data and analytics conferences scheduled for 2018. Each listing includes dates, locations, social media connections, agenda highlights, and pricing. The event websites provide a lot more detail, but this summary can help you create a travel short list of your own.
A couple of notes before you dig in:
If you have the time and budget to attend only a single conference in 2018, make it one from this section. These events are well established from respected organizations. They pack a lot of depth into the agenda: speakers, training, workshops, and lots of chances to meet and mingle.
TWDI conferences focus on hands-on workshops, presentations, and boot camps, emphasizing practical skills as well as the latest data and analytics trends.
Each conference is staunchly vendor-agnostic, so none of the sessions are a hard sell in disguise. You can still get conference swag from vendors, but you have to go to the exhibit hall rather than the course rooms.
More than 50 sessions are offered in full- and half-day time periods, including four introductions to basic data science concepts. Examples of other sessions include "Data Virtualization: Solving Complex Data Integration Challenges," "Hands-on: Introduction to Data Mining with R," and "Data Storytelling: Bringing Data to Life."
Keep up with the latest in IT-driven business innovation with enterprise.nxt's weekly newsletter.
Each TDWI conference is paired with a TDWI Leadership Summit, which aims to give business leadership insights into creating data-driven companies, what to do with the data they have, and how to build and manage data science teams.
Albert Valdez, VP of learning solutions at Senturus, wanted to learn whether data science was becoming the new buzzword (to replace big data), so he attended the data science boot camp sessions at the TDWI conference in August to see what's what. He was not disappointed, saying he benefited from the "clarity that I enjoyed upon graduating from the TDWI Data Science Bootcamp," some of which was led by "a bonafide data scientist, Dean Abbott."
Who should attend: Data analysts, data warehousing and data integration specialists, architects, designers, and developers. The leadership summits may be of interest to CIOs, line-of-business management, chief data officers, BI directors, and data warehousing directors.
Gartner conferences are not inexpensive. But it’s the best way to hear from Gartner analysts about looming trends, best practices, and recommended vendors. Most of the speakers for the 2018 event are Gartner analysts, except for two highlights: author Daniel Pink and inspirational speaker John O’Leary.
The agenda is always extensive, and at this one, there are a whopping eight tracks to follow. They cover several aspects of data and analytics, with the common thread being how to implement best practices that turn your company into a data-driven machine.
Gartner works to serve specific industries, so it offers vertical tracks including insurance, the public sector, healthcare payer and provider, and banking and securities.
Who should attend: Chief data officers at large organizations, people responsible for data and analytics, and aspiring IT leaders.
2018 marks the 22nd Enterprise Data World conference. As with its predecessors, its attention is on data management from both a technical and business perspective, with an emphasis on the business end.
Enterprise Data World is a relatively long event, with a six-day program that includes introductory, intermediate, and advanced sessions. That makes it suitable no matter how much you already know, everything from "Data Curation: A Coordinated Practice for Data Management (Introductory)," to "Data Quality Assessment and Measurement (Intermediate)," to "Data Modeling for Document and Graph NoSQL Databases, Hands-On (Advanced)."
The conference also includes sessions for non-technical attendees, such as "Data Management's Dirty Little Secret" and "Making Metadata Valuable: ExxonMobil’s Journey Collecting and Cataloging Metadata."
Who should attend: Midlevel and senior managers, data and information architects, data scientists, and data engineers.
Formerly known as Strata + Hadoop World, the Strata Data Conference series is put on by O'Reilly and Cloudera, and focuses on using data to gain business advantage.
In 2017, Chad Carson made his fifth trip to Strata in New York. "I enjoyed the rich discussions of interesting applications," he says, "and how people are using big data to solve real problems in the real world."
There's a lot going on at these events, including:
There is a strong technical focus to the Strata Data Conference. To get the most out of it, a strong technology background is required.
The San Jose event also hosts the Strata Business Summit, aimed at business leaders who are building data-driven companies. The sessions for this co-located event are mostly in the keynote presentation format.
Who should attend: Data-driven designers, data engineers, data scientists, developers and database professionals, researchers and academics, and enterprise architects.
Since KDD 2018 will be the 24th KDD conference, you can expect a well-polished event. The event spans five days, and according to Tawni Burger, a software engineer and data science enthusiast, it provides a wealth of knowledge in many areas, from the latest data science research to data mining, big data, and predictive analytics.
While the agenda for KDD 2018 has not yet been released, KDD 2017's program reveals the event’s depth and breadth. The conference starts with two days of tutorials (such as "Data Mining in Unusual Domains with Information-Rich Knowledge Graph Construction, Inference, and Search" and "Smart Analytics for Big Time-Series Data") and workshops (such as "Data Driven Discovery" and "Big Data, IoT Streams and Heterogeneous Source Mining").
The main KDD conference was three days long in 2017, with hands-on tutorials, presentations, and keynotes from full-time academics from institutions including Harvard and UC Berkeley. One track is Applied Data Science Invited Talks, wherein industry leaders from companies like Facebook, Target, and Bosch join data science educators to discuss topics that cover the bleeding edge of data science. KDD 2017 sessions included "It Takes More than Math and Engineering to Hit the Bullseye with Data" and "Planning and Learning under Uncertainty: Theory and Practice."
Who should attend: Data scientists and engineers who seek exposure to cutting-edge research in the data and analytics world as well as exposure to how theory is put to practice at some of the world's largest companies.
Some conferences are of interest to a narrow focus, when you want to know about a given area of big data and analytics in depth.
The ACM Web Search and Data Mining conference is an academic-style conference that seems to do it up right. While the program for 2018 is not yet available, 2017's agenda shows its mix of technical presentations and business networking.
The first day has tutorials (such as "Social Media Anomaly Detection: Challenges and Solutions" and "Neural Text Embeddings for Information Retrieval"); a startup day during which researchers and startups share ideas and meet future employers or employees; and a doctoral consortium.
The next three days of the conference are filled with the following:
Perhaps this tweet from Sylvain Peyronnet sums up the conference best: "#wsdm2017 great science great location great beer and that's it folks."
Who should attend: Data scientists and people interested in new research about data mining, natural language processing, neural networks, and other academically-facing topics.
If open source rocks your world, then you should try to make one of these three events next year. As the name implies, the Open Data Science Conferences focus on open source data science tools, libraries, and languages. The four-day conference has 200 speakers addressing a wide variety of data science topics, including recommendation systems, transfer learning, image classification, and self-driving vehicles. Certainly you can look for deep expertise, with past speakers including Ted Kwartler, assistant vice president for innovation at Liberty Mutual; Moon soo Lee, CEO at NFLabs; and Tanya Cashorali, data analytics consultant at TBC Analytics.
You don’t have to be an old hand at data science to get something out of ODSC. As Elizabeth Albee tweets, "Good stuff for nubies and experts alike." If you want to network, this is your event. As one attendee wrote, "Loving being surrounded by data geeks with diverse backgrounds at @odsc."
Who should attend: Engineers seeking to beef up their data science skills, students and professionals looking for jobs, and employers looking to hire.
Organized by Database Trends and Applications and Big Data Quarterly, the Data Summit focuses on four areas: Digital Transformation; Competing on Analytics; Moving to a Modern Data Architecture; and Building the Data-Driven Future.
Data Summit 2018 is primarily about high-level topics of interest to C-level IT managers and senior engineering staff. For instance, last year's summit featured:
Who should attend: Aimed at the C-suite plus analysts, scientists, and business execs in industry and government.
The Predictive Analytics World event in 2018 in Las Vegas is actually a number of co-located industry-vertical events, including PAW Business, PAW Financial, PAW Healthcare, PAW Workforce, and PAW Manufacturing. This conference will be so big, the company is calling it Mega-PAW.
While the full agenda hasn’t been announced, a number of workshops are already in the works, such as "The Best of Predictive Analytics: Core Machine Learning and Data Science Techniques" and "R Bootcamp: For Newcomers to R."
Who should attend: IT and business managers responsible for analytics, data, and strategy.
Among the most popular tools for technologists working with big data is the R programming language. If that’s you, this conference may be of particular interest. useR!, an event for the R user community, focuses on R programming as well as general statistics topics. If you work with R, or want to start doing so, you should give serious consideration to this event—assuming you’re somewhere near Brisbane or can convince the boss to let you travel to Australia.
If 2017 is an indication, the event is a solid mix of tutorials and social opportunities.
Keynotes included discussions of topics of general interest to statisticians, such as "Structural Equation Modeling: Models, Software and Stories," as well as user R-related topics, such as "Parallel Computation in R: What We Want, and How We (Might) Get It."
The event highlights the latest and greatest R innovations. Bert Jehoul tweeted, "Good idea to hand out sunglasses at #useR2017, with all those shiny - apps popping up in the #rstats #rshiny world." Meanwhile, Max H. Nierhoff's tweet revealed attendees' enthusiasm for new tools: "Awesome extensions for the #shiny framework with the shinysense package by @NicholasStrayer #useR2017 #rstats."
But innovation is not all that's going on. As you can see from Gergely Daróczi's tweet, useR! is also an opportunity to network: "It was so great to meet in person and chat with you all good old and new #rstats friends at #useR2017 – hope to see you soon!"
Who should attend: Statisticians and data scientists who work with R or plan to do so.
The Joint Statistical Meetings event is a gathering of 10 statistics institutes, societies, and associations. If your analytics interest is primarily in the statistics industry, you’ll find this 2018 conference, with the theme #LeadWithStatistics, of particular interest. Organizers say it will include 6,500 attendees, 1,000 students, 600 sessions, and 100 exhibitors.
The 2017 agenda reveals the richness of this event with opportunities for continuing education on "Regression Modeling Strategies" and "Construction of Weights in Surveys;" computer technology workshops on "Bayesian Analysis Using Stata" and "Applied Data Mining Analysis: A Step-by-Step Introduction Using Real-World Data Sets;" personal skills development classes like "Career Development: Statistical Soft Skills: They’re Essential" and "Preparing Statisticians for Leadership: How to See the Big Picture and Have More Influence;" and roundtables such as "Non-Inferiority Trials for Efficacy and Safety" and "Why Do Students Hate Statistics?"
According to Altea Lorenzo, collaboration seems common: "My #JSM2017 highlight is the incredibly kind help from colleagues who even shared their code."
Who should attend: Statisticians and data scientists.
Featuring the latest research in the data mining field, the IEEE International Conference on Data Mining is where you go to discover the bleeding edge of data science research. ICDM is primarily an academic conference with first-time presentations from PhD students as well as sessions led by full-time professors on original concepts and approaches.
If you love acronyms, you'll love this conference! That's because, as you can see on the 2017 program, each item on the schedule is preceded by its very own abbreviation. Acronyms aside, the 2017 agenda was chock full of interesting sessions including:
There are a lot of benefits for students attending this event, but the biggest might be the opportunity to present at the PhD panel. The reception seems warm, a good place to start for students, with some major bonding moments with mentors.
Note that the IEEE ICDM event should not be confused with the Industrial Conference on Data Mining taking place in New York July 11-15.
Who should attend: Researchers, students, and application developers.
This final section lists smaller or newer conferences that may be the best events you never heard of.
The core philosophy of The Data Science Conference is "to provide a vendor-free, sponsor-free, and recruiter-free conference for professional data scientists." Judging from what 2017 attendees had to say, the conference stayed true to its values.
This is the "event for practicing data scientists to share, learn, and grow together without the distraction of vendors, recruiting or sponsorships," says Ivan R. Judson, a conference goer from Microsoft.
The TDSC is "by data scientists for data scientists," says Alessandro Panella, from Facebook. "TDSC is a great place to get an in-depth update on the state of industry, learn best practices, and further the understanding of data science."
The 2018 event promises its usual stellar lineup of speakers, including Gregory Duncan, chief economist and chief statistician at Amazon, who will speak on "Econometrics and Machine Learning: A Reintegration;" Jing Xi, director of data science at Expedia, whose topic is "How Deep Learning Can Help Improve Expedia Bidding Algorithms;" and Mario Jimenez, head of risk analytics at Nasdaq, who will address "Automation of Corporate Credit Risk Analytics."
Who should attend: People involved with data science, data mining, big data, machine learning, artificial intelligence, and predictive analytics.
The Data Science Congress is India's answer to the question: "How can we share best practices, case studies, and innovations in the data science field?" It offers keynotes, an exhibit floor, and research paper presentations.
Who should attend: IT managers and data scientists.
Big Data Day LA is a volunteer-run free (or very low cost) event that started with just over 250 attendees in 2013 and grew to 1,550 attendees in August 2017.
With nine concurrent tracks at this one-day conference, you could dive into areas including big data ("Extending Analytic Reach, from the Warehouse to the Data Lake"); data science ("Deriving Conversational Insight by Learning Emoji Representations"); Hadoop, Spark, and Kafka ("A Tale of Three Apache Spark APIs: RDDs, DataFrames and Datasets"); and use-case driven sessions ("Data Is Cheap; Strategy Still Matters"). The keynote speakers come from big companies such as Google, The New York Times, and Warner Brothers.
That makes this an appealing event for anyone in Southern California. You won’t even have to ask the boss for a ticket budget.
Who should attend: Data scientists, software developers, system architects, researchers, business analysts, data engineers, technical leads, IT managers, business strategists, and data analysts.
This article/content was written by the individual writer identified and does not necessarily reflect the view of Hewlett Packard Enterprise Company.