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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

Accompanying the massive growth in sensor data (from ubiquitous IoT devices, including location-based and time-based streaming data), there have emerged some special analytics products that are growing in significance, especially in the context of innovation and insights discovery from on-prem enterprise data sources.

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The Power of Graph Databases, Linked Data, and Graph Algorithms

Rocket-Powered Data Science

The training data and feature sets that feed machine learning algorithms can now be immensely enriched with tags, labels, annotations, and metadata that were inferred and/or provided naturally through the transformation of your repository of data into a graph of data.

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Four starting points to transform your organization into a data-driven enterprise

IBM Big Data Hub

IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance. The data governance capability of a data fabric focuses on the collection, management and automation of an organization’s data. Data science and MLOps.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format. To do this at scale, you have to use AI/ML services for decision-making.

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Themes and Conferences per Pacoid, Episode 10

Domino Data Lab

Co-chair Paco Nathan provides highlights of Rev 2 , a data science leaders summit. We held Rev 2 May 23-24 in NYC, as the place where “data science leaders and their teams come to learn from each other.” If you lead a data science team/org, DM me and I’ll send you an invite to data-head.slack.com ”.

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The Gartner 2021 Leadership Vision for Data & Analytics Leaders Webinar Q&A

Andrew White

As such a head of analytics, BI and data science may emerge. Are you anticipating continued separation of “BI/Analytics” teams from “Data Science” teams or are those roles merging in the years ahead? Many data science labs are set up as shared services. That’s the idea.