Remove Metadata Remove Metrics Remove Modeling Remove Prescriptive Analytics
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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

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

AWS Big Data

The following figure shows some of the metrics derived from the study. 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. Organizations using C360 achieved 43.9%

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Build an analytics pipeline that is resilient to schema changes using Amazon Redshift Spectrum

AWS Big Data

You can read from all the ingested data files at a specified Amazon S3 location with different schemas through a single Amazon Redshift Spectrum table by referring to the AWS Glue metadata catalog. In this post, we showcased how you can derive metrics from common atomic data elements from different data sources with unique schemas.

IoT 94
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Themes and Conferences per Pacoid, Episode 10

Domino Data Lab

We had data science leaders presenting about lessons learned while leading data science teams, covering key aspects including scalability, being model-driven, being model-informed, and how to shape the company culture effectively. Data science leadership: importance of being model-driven and model-informed.

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A Guide to Data Analytics in the Travel Industry

Alation

They may also suffer from data duplication, which undermines their analytics models. How is data analytics used in the travel industry? So much is automatic — the metadata extraction, curation, labeling, query log ingestion, and building out the lineage — it’s a big help,” says Leonard Kowk, senior data analyst.

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What Is Data Intelligence?

Alation

It includes intelligence about data, or metadata. The earliest DI use cases leveraged metadata — EG, popularity rankings reflecting the most used data — to surface assets most useful to others. Again, metadata is key. Data Intelligence and Metadata. Data intelligence is fueled by metadata.

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

Andrew White

Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. Decision modeling (one of my favorites). Explore in dialogue decisions and outcomes rather than focus on data and analytics asked for. Try some gamification?