Big data collaboration platforms catalyze organizations to overcome barriers to cross-functional, organizational collaboration.
Now before your business brains time out and your eyes glaze over, take a few deep breaths and read on. No one gets a free pass out of the Big Data conversation anymore just because you are not technically or operationally inclined. Yet.
That’s why I attended the Strata Hadoop conference in NYC late September. Yeah. This girl when There and worked (and had a heck of a lot of fun) with Them.
This annual event is one of the largest meetings of data minds. The meeting attracts movers and shakers in the big data, machine learning and artificial intelligence developer and data scientist communities.
Good things happen when data scientists collaborate with not only applications developers but with everyone else throughout the enterprise.
Open source software collaboration can provide greater diversity of business outcomes if you take action on insights.
The conference showcased why major players like Cloudera, IBM, SAP and Intel, for starters, are pursuing open source big data collaboration platforms for problem solving. Open source collaboration models develop software programs and application interfaces with input from multiple independent resources.
As a result, software design benefits from a greater diversity of scope and perspective than a single enterprise or corporate culture would offer. Hmmm. Read that sentence again. Except replace the words “software design” with engineering, operations, business, finance, human capital.
What are the implications of developing, taking action on and implementing an open source mindset into your own business model?
Trusted Analytics Platform , or TAP, gets everyone throughout the organization focused on innovative problem-solving.
At the conference, I became more familiar with many big data and analytics platforms. I found the TAP big data collaboration platform particularly intriguing. Its mission is to make it “easier for developers and data scientists at enterprises, Cloud service providers and system integrators, to collaborate by providing a shared, flexible environment for advanced analytics in public and private Clouds.”
What engaged me was that data scientists and developers using the TAP platform found themselves more readily mixing with, and being understood by, non-technical professionals across the enterprise. With so many organizations wrestling to incorporate big data and predictive analytics in decision making, the proof-of-concept business cases for TAP were a refreshing break from legacy mindset.
Any time a big data collaboration platform starts poking holes in systemic corporate silos, they have my full attention.
One TAP big data collaboration pilot project features Penn Medicine. Michael Draugelis, chief data analyst, is using the platform to work with clinicians to predict in-patient outcomes across various diagnoses. Rather than only creating predictions for groups of patients, the data also yield customized, personal, per-patient predictive insights.
Another pilot project, at Icahn School of Medicine at Mount Sinai, deploys the TAP big data collaboration platform to accelerate the rate of discovery of new therapeutic modalities.
A particularly impactful TAP presentation involved financial data. Financial transactions, especially those involving stock trading, can generate nearly 7 million data points per second. That is a lot of data to capture, tag and analyze. What intrigued me were the distribution graph patterns. They resembled the same type of data volume and velocity impacting predictive maintenance and overall equipment efficiency (OEE) within smart manufacturing environments.
Take action from big data collaboration platform insights. Now.
Depending on where we sit around the business table, we all see the same things differently. When an organization becomes more “open source” about cross-functional collaboration, the entire enterprise benefits from hybridized perspectives.
That is a good lesson learned from the Big Data ecosystem.
At the Strata Hadoop conference, Brian Hopkins, VP and Principle Analyst at Forrester Research, gave a presentation about developing the insights-driven business. He emphasized that when enabling the business to become data-driven, you can spend all the money you want on new tools for data capture and analytics.
Then what happens?
Hopkins feels the problem isn’t big data or analytics. The problem is lack of organizational action. Deciding to do nothing is not any form of taking insight-driven actions at all.
One play from my Playbook encourages data-driven and insight-driven organizations to gain competitive advantage through cross-functional collaboration between the business types, the operations types and the data types of folks. #KnowYourData
Another play encourages the organization to become knowledgeable about the data hiding within your organization. Open source your mindset and cross-pollinate your thinking by poking holes in legacy corporate silos which sequester data and people in departmental fiefdoms.
How will your own team take action to #KnowYourData ? How could you begin to apply data-driven insights more effectively when working with internal and external client teams? What are you waiting for? Take action!
Babette Ten Haken writes, speaks and coaches about customer success for customer retention. She traverses the interface between human capital strategy for hiring and developing collaborative technical and non-technical teams. She serves manufacturing, IT and engineering intensive companies. Babette’s playbook of technical / non-technical collaboration hacks, Do YOU Mean Business? is available on Amazon.