The top 5 things we learned from the world’s leading data experts at Strata + Hadoop World NYC

October 04, 2015 by Madison Jacobs

We enjoyed every big data filled moment of Strata + Hadoop World in NYC last week and wanted to share our top 5 takeaways from the conference.

1. Technology is changing very rapidly around us, but people stay the same. - Hilary Mason, Founder of Fast Forward Labs

“In reality, data isn’t always a technology problem… it’s a people problem,” Hilary said. Hilary reminded us that even though technology is always changing and adapting, people stay the same. The key to success with data is not only to utilize the right technology, but also to get all the stakeholders (technology-facing and business-facing) within an organization to believe in data and its ability to revolutionize the way the business operates. “Everyone has to be bought in,” Hilary said. Hilary also recommends that organizations find a strong data leader who can speak to and align the business and technology departments within a company. Without a capable leadership team who can foster a data-driven culture, success with data will be extremely difficult to obtain.

About Hilary: Hilary Mason (@hmason) is the Founder of Fast Forward Labs (@fastforwardlabs) and the Data Scientist in Residence at Accel (@Accel). Read our recap of Hilary's entire presentation here.

2. We shouldn’t underestimate the complexity of artificial intelligence (AI). - Jana Eggers, CEO of Nara Logics

Jana explained in her presentation that AI isn’t something businesses should feel threatened by (after all, it is just algorithms), but it is something that organizations should begin to incorporate into their processes. When thinking about how to onboard AI technologies, Jana recommends that businesses partner with startups or people who have studied AI and understand it. “We know your business,” Jana said. “You need to make sure that you are bringing in people that really understand the tools that are needed and can figure out how to apply them to your business. Complexity requires expertise.”

About Jana: Jana Eggers (@jeggers) is the CEO of Nara Logics (@NaraLogics). She’s a seasoned tech executive/computer scientist that’s focused on products and the messages around them. Read more about Jana here.

3. Predictive analytics on big data is improving medical decision making. - Michael Draugelis, Chief Data Scientist at Penn Medicine

Michael’s presentation explained that even in this era of intense medical breakthroughs, many illnesses still evade accurate and timely diagnosis. Clinicians’ must often rely on static diagnostic guidelines, that result in late care and too many false alarms. Half of all heart failure patients can go undiagnosed. Patients with chronic illness, like congestive heart failure, slip through the cracks, missing lifesaving education and treatment. Michael shared how Penn Medicine (in partnership with Intel) are collaborating on an open source analytics platform to revolutionize health care. By using more data and advanced analytics to predict patient illness, clinicians can increase detection rates, reduce care costs and most importantly, save lives (1).

About Michael: Michael Draugelis (@mdraugelis) is the Chief Data Scientist at Penn Medicine (@PennMedicine) and is working to create data-driven products that change the way patients are treated and cared for. Watch the video of Michael’s keynote presentation here.

4. Insurance companies are empowering non-technical employees to use data. - Kristi Marotta, Competitive Intelligence Consultant at Allstate

During Kristi’s talk, we learned that Allstate is leveraging advanced big data technologies to give employees access to the data they need to better serve their customers. Kristi explained that Allstate has millions of policyholders and that all of the data for each policy is kept in multiple areas. To get a complete view of each policy, it would take a week to aggregate the data, making it impossible to get a real-time view of the customer. Because their legacy systems were so slow and inefficient, important customer data, that should be updated frequently, was only updated a couple of times each year. So in 2011, Allstate set out to create an “encyclopedic” data information resource that would help data users of all types -- developers, business users, data scientists, ETL specialists -- gain a single centralized place where they could quickly and easily answer data questions without fear of bandwidth constraints or shallow aggregate tables. Kristi shared that Hadoop, paired with self-service tools like Tableau, have helped Allstate make more data-driven decisions (2).

About Kristi: Kristi Marotta is a Competitive Intelligence Consultant at Allstate (@Allstate) and an actuarial scientist that’s also a really good cook.

Want to learn how insurers can leverage big data analytics to overcome industry stagnation and encourage growth and opportunity in insurance? Check out this white paper: Bringing Big Data to Life for Insurance.

5. Data quality matters. - Several data experts

During many of the presentations we attended at the conference, data experts spoke about the importance of data quality. Many enterprises struggle with analytics because the data they are utilizing is not high-quality, meaning that companies can’t draw reliable conclusions from the data they are analyzing. High-quality data should be complete (not missing important pieces of information, accurate (no presence of erroneous data points), available (accessible by all data users, technical and non-technical), and timely (always up date). Data-quality related business problems cost companies millions of dollars annually because of lost revenue opportunities, failure to meet regulatory compliance or failure to address customer issue in a timely manner (3). When capturing data to be used in predictive analytics, is important that business choose technologies that help them maintain data control.

You can check our more presentations from Strata + Hadoop World in NYC here.

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