|News & Updates
| February 26, 2012
Data 2.0 Summit
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April 30th, 2013
Data 2.0 Is Now Media, Committees, and Conferences.
We founded the Data 2.0 Summit 2 years ago with the goal of making data more accessible.
2 years later we’re continuing that mission by launching a new hub of Data 2.0 activity on Data2x.com. Beyond simply being a hub of activity across Data 2.0 Summit, DataWeek, and DeveloperWeek, Data2x will be a catalyst for thought leadership articles and yearly reports published by our committees across Big Data, Social Data, Open Data, and Data Science.
This new site has 4 purposes:
1 COMMITTEES AND REPORTS: Data 2.0 will act as an association for organizing leaders in the data innovation industry. Each committee will publish an annual report on such topics as Data Portability, Data Marketplaces, and Climate Change Data Science. The purpose of these reports is to draw attention to industry-based initiatives and future outlooks.
2 UPCOMING EVENTS: This will allow the community to keep track of our upcoming conferences on the right-hand sidebar.
3 DATA 2.0 NEWS: The homepage and news page will provide a stream of news relating to the data innovation industry, our conferences, and major updates from our Data 2.0 partners.
4 MEMBER AND PARTNER PROGRAMS: (To be launched this year) Member and partner programs will give your company access or discounts to our year of data and developer conferences, paid annual reports, and publicity through the Data 2.0 community.
4 Trends in 2013 Data Innovation
This article is also available on Data2x
1. Big Data will be friendlier.
Many of the current well-known big data technologies are chiefly “T2T” or “technology sold to other technology people” such as Vertica (Acquired by HP), Cloudera, Teradata, MongoDB, CouchDB, and many of the ‘infrastructure’ companies shown on this infographic. From Hadoop, Hive, and HBase to NoSQL or NewSQL, big data is scary to non-wizards.
We at Data 2.0 think Volume, Velocity, and Variety aside - there needs to be a revolution in the friendliness of big data. That is the message behind new companies like Continuuity, Flow, Birst, and Domo; that you do not need to be a developer to get value out of big data.
I find Continuuity especially interesting. Just as platforms like Heroku or dotCloud deploy app infrastructure as a service, I can imagine a new ecosystem of players that deploy big data infrastructure as a service for non-wizards.
2. The Data-Driven Enterprise will change how we work at companies.
Lets assume that the cost of storing, searching, analyzing, and moving around big data continues to fall. How will this change the dynamics of a company?
I would consider data-driven decision-making powered by business intelligence apps like Tableau or GoodData to be a decade-long trend, so I’ll focus this trendspotting on big social enterprise data.
Apps like Badgeville, Socialcast, Yammer, Huddle, or Asana (and on the flip side apps like Workday) are themselves amassing data on how we work - and the next step is for these “Enterprise 2.0” applications to give us more intelligence on the social dynamics and productivity dynamics of employees or teams. More data on work dynamics means more gamification, incentives, reputation management, and social ‘credit’ for the work we do - all driven by an emerging class of enterprise 2.0 data.
3. More startups will essentially be “Data Startups”
Callinize, the winner of our DeveloperWeek 2013 hackathon last February 1-3, is actually a mashup of 4-6 different data sources like Mashape, Salesforce, and RapLeaf. The end user might not know it, but the power of Callinize to grab intelligence on whoever is calling you (before you answer the phone) is based on the fact that Callinize is really a mashup of API’s. It’s a data startup.
Across the landscape of all web and mobile startups, the new competitive edge is the ability to leverage more 3rd party API’s. A few companies that either provide API’s or consume multiple API’s have recently received funding in the past 12 months including Identified (+$21m), Stormpath ($9.7m), and Adaptly (+$10.5m) to name a few.
More startups will be “data startups” (companies whose chief asset value is based on what they can do with API’s) because the API ecosystem is the new competitive edge. If you utilize 3rd party API’s (or provide 3rd party API’s) better than your competitors, you will win. And investors are recognizing that.
4. The rise of Data Science-as-a-Service and Algorithms-as-a-Service
Let’s think about the stages of enterprise decision-making.
Step 1: Collect the historic data used for making predictions using software / storage
Step 2: Analyze / visualize the historic data so you can find trends / generate reports
Step 3: Use the data and analytics to make predictions about the future
Whereas steps 1 and 2 are already available via API’s from technology providers, we are only starting to unlock the potential of step 3.
Startups such as Precog, Wise.io, Prior Knowledge, and Algorithms.io promise a new frontier of predictive analytics and data science - which in a sense is a subset of analytics dealing with the modeling of future events based on the logic of an algorithm.
These services do not replace the importance of a data scientist to build predictive models, however, they do ‘democratize’ certain use cases of data science to the point that any online shopping cart can recommend what DVD’s you may want to buy based on previous purchases - or any company can model its 2013 / 2014 financials off of better future outlook financial algorithms.