The document discusses the evolution and significance of big data, highlighting the transition from traditional structured data to native data formats and the importance of governance within data strategies. It emphasizes the role of cloud technology and IoT in transforming dispersed data sources, making data intelligence teams more accessible and agile. The key to achieving new revenue opportunities lies in digital transformation and collaboration, where applied data science enables insightful decision-making and operational efficiency.

1. Christine
Trainor
Director of Data
Intelligence

2. Big Data the Myth and the Reality
 Big Data what is it?
 The evolution from traditional structured data to native.
 Native format of data
 Extract transform and load to extract load and
transform
 Governance of Data must be part of your strategy

3. Cloud and Industry of Things (IoT)
 Dispersed data sources are transformed in the cloud.
 Cost is now affordable for all
 Challenge of what is next once your data is in a
distributed world
 You still need to digitally transform your data to insight
to find value.
 Data Intelligence teams now have easier access with
virtual machines

4. Applied Data Science
 Wrangling data in the wild is key.
 Finding the Data in dispersed environments
 Conversing with the expert to find the value.
 Strategy for Minimal Viable Services
 The agile approach to digital visualize data

5. Unlocking Profitability and Performance
 Strategy is the key to unlocking new revenue opportunities increase
profitability and increased performance.
 Minimal viable service
 agile is key to the team
 Digital Transformation happens in collaborative environment
 Put App in hands of the client
 Applied data science is rooted in the voice of data and the ability to
develop algorithms and train models
 Once you have to taught the data to talk and answer questions you
might not have known to ask you are on the path
 Empowering the human in the loop not replace them

6. Q&A