Collaborate to foster cognitive disruption


Think of data science as the place innovations originate in today’s world. The people who are transforming established industries, and even spawning new ones, generally use the tools and techniques of open data science to power their efforts.

Open analytics are the foundation of disruptive application development in the 21st century economy. Speedy, agile, creative development comes when people from many backgrounds, roles and skill sets use tools such as Apache Spark, R and Apache Hadoop to build innovative applications that are deployed on cloud, mobile, social, Internet of Things and other next-generation platforms.

Teaming up on innovation

Open teams can unlock creativity in data science, as long as everybody pools their skills and specialties with a clear focus on driving disruptive outcomes. The key roles in these teams are the following: 

  • Data scientists can use data science tools for teasing out the insights they’re looking for and for making those insights useful immediately through applications, visualizations and other consumables.
  • Data engineers can build data processing pipelines that leverage machine-learning, stream computing and other capabilities to ingest data from disparate sources, aggregate and cleanse it, and deliver it downstream to smart applications of all sorts.
  • Application developers can use algorithmic capabilities to endow their apps with cognitive capabilities that learn from fresh data and take actions that are continually optimized in keeping with contextual, predictive and environmental variables.
  • Business analysts and subject-domain specialists can use statistical exploration tools to answer domain-specific questions quickly, easily and without need of IT assistance.

http://www.seenews.info/wp-content/uploads/2016/09/openecosystem_embed.jpgTooling the data science effort

These teams’ productivity pivots on open-source analytics tools such as Spark and R, which help deliver the following value in collaborative initiatives:

  • Facilitating the democratization of self-service data analytics development across enterprises and communities, especially when these programming tools are accessible from within teams’ primary development workbench
  • Enabling distributed teams to address bigger data-centric problems and reap commensurately larger business results more rapidly than ever, especially when accessed in a shared, public cloud service
  • Accelerating development of high-performance analytics applications rapidly, flexibly and easily, especially when using them with browser-based notebooks that support code, text, interactive visualization, math and media
  • Providing a unified execution model for big data processing and analytics capabilities all in one environment, especially when deployed in conjunction with Hadoop, NoSQL databases and other cloud-based data platforms
  • Reducing the amount of code and number of tools needed to combine a deep stack of cognitive capabilities in a single application, especially when used in conjunction with rich libraries of machine learning, streaming analytics, graph computing, natural-language processing and other algorithms
  • Allowing teams to refine analytics applications interactively and iteratively, especially when used in conjunction with data and model governance features that are integrated into the data lakes around which the data science development lifecycle revolves

Learning more in the data science ecosystem

Attend the Strata + Hadoop World 2016 conference the week of 26 September 2016, to see how IBM helps organizations empower their analytics development teams with collaborative tools optimized for next-generation data lakes built on Hadoop, Spark and other key technologies. And while you’re in New York for Strata, also attend the IBM DataFirst Launch Event, Tuesday evening, 27 September 2016, that takes place at Hudson Mercantile, 500 West 36th Street—just a few blocks from Jacob Javits Center. The event unveils new ways to put data to work on organizations’ path to become cognitive businesses.

Or, if you can’t make it in person to the DataFirst Launch Event, watch the event’s livestream. When you register for the livestream, you’ll receive a calendar update and login link. Also be sure to follow the event on Twitter at @IBMBigData and using the hashtag #DataFirst. 

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