Editorial Calendar

Datanami's 2017 Editorial Calendar At-A-GlanceWritten and edited by the leading journalists in the field of big data, Datanami offers unmatched insight, analysis and up-to-the-minute information about emerging trends and solutions in big data. From networking to applications, or business to government, we have you covered. So keep up with the latest themes and events in big data analytics with Datanami’s 2017 editorial calendar.


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Apache Spark

Neural Nets


Big Data Innovation Summit: January 28-29 



Artificial Intelligence – Thanks to improvements in hardware and software, the AI revolution officially upon us, resulting in new levels of personalization.

Data Visualization – The ability to “see” data is critical to our ability to find patterns within it.

Industry Focus: National Security


AnacondaCON 2017: February 7-9

Spark Summit: February 7-9

Predictive Analytics Innovation Summit: February 22-23



Hadoop and Friends – What is Hadoop? By last count there were more than 30 projects related to Hadoop. We’ll take a look at the core projects and how the ecosystem is evolving

Autonomous Cars – For many people, AI will finally become real when cars can drive themselves. We’ll check out the latest in self-driving vehicles


Gartner Data & Analytics Summit: March 6-9

Strata + Hadoop World: March 13-16

Leverage Big Data + EnterpriseHPC 2017: March 19-21

ReWork Machine Intelligence and Autonomic Vehicles Summit: March 23-24



Real-Time Analytics – With the rise of IoT and machine data, the ability to make sense of data in real time has never been more important.

NVMe Storage – The latest news and trends to watch out for in the area of NVMe storage

Industry Focus: Life Sciences


SAS Global Forum: April 2-5

Big Data Innovation Summit: April 19-20

Flink Forward: April 10-11



Deep Learning – As one of the core building blocks for AI, deep learning allows us to leverage big data like never before

Big Data in Human Resources – How is big data analytics impacting the human resources profession? We’ll take a deep dive into the topic.


GPU Technology Conference: May 8-11

Deep Learning Summit: May 11-12

Predictive Analytics World Business: May 14-18

Open Data Science Conference East: May 25-27



Text Analytics – Despite the rise of emojis, humans still do much of their communication via good old text. We’ll look at the latest in the world of text mining.

In-Memory Computing – RAM is often seen as the final frontier in the world of fast data analytics. We’ll examine the available options for in-memory computing.


MongoDB World: June 20-21

Spark Summit: June 5-7

Hadoop Summit: TBD



Predictive Analytics – What are the major types of predictive analytics, and what do organizations use them for? We’ll dive into the topic

Hacker Hunting – Cybercriminals are wreaking havoc across industries. We’ll see how top organizations are using big data technology to take the fight to cybercriminals.

Industry Focus: Financial Services


MLDM 2017: July 15-20



GPUs and FPGAs – We’ll examine how GPUs and FPGAs are helping leading-edge organizations to analyze big data.

Data Science Back to School –As college students head back to school, we’ll take a look at the big data analytics programs of top universities around the country.



Graph Analytics – What big data problems are graph databases best at solving? We’ll dive into the topic with real-world examples.

Data Prep – Without good quality data, analytics suffers. We’ll investigate the latest tools and techniques data scientists are using to prep their data.


MLconf Atlanta: September 15

Strata + Hadoop World: September 25-28



MPP Databases – Column-oriented databases are very good at solving a core set of data warehousing problems. But how much longer will they hold the advantage with the rise of SQL on Hadoop?

IoT Analytics – Machine data is projected to grow immensely in the coming years. How will organizations take advantage of it?

Industry Focus: Energy


Oracle OpenWorld: October 1-5

Tableau Conference: October 9-13 Las Vegas

Teradata Partners: October 22-26



NoSQL Databases – Flexible, scale-out databases are growing much faster than their relational counterparts. We’ll take a look at the state of the market and challenges NoSQL databases face.

Big data security – Collecting big data brings big risks. We’ll cover best practices for securing big data.


MLconf SF: November 10

AWS re:invent: November 27 – December 1



Big Data for Public Good – We’ll explore use cases for big data analytics that benefit humanity

Open Source Software – Open source has emerged as a key enabler for big data analytics.


January 2018:

Data Governance – Succeeding in big data is not a hit and miss affair. It requires a carefully planned and executed strategy, including data governance.

Big Data on Cloud – We’ll take a look at what’s happened in the cloud big data scene over the past year.

Industry Focus: Healthcare


For questions or pitches on related stories, please contact: editor@datanami.com

For sales inquiries, please contact: promote@datanami.com


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