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Understanding the Differences Between Data Lakes and Data Warehouses

Smart Data Collective

Data lakes and data warehouses are probably the two most widely used structures for storing data. In this article, we will explore both, unfold their key differences and discuss their usage in the context of an organization. Data Warehouses and Data Lakes in a Nutshell. Target User Group.

Data Lake 139
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The Data Scientist’s Guide to the Data Catalog

Alation

Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming.

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Graphs on the Ground Part I: The Power of Knowledge Graphs within the Financial Industry

Ontotext

This article will examine the world of financial services and look at how knowledge graphs enable organizations to derive more value from the data they already possess. A knowledge graph uses this format to integrate data from different sources while enriching it with metadata that documents collective knowledge about the data.

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Top 10 Key Features of BI Tools in 2020

FineReport

Metadata management. Users can centrally manage metadata, including searching, extracting, processing, storing, sharing metadata, and publishing metadata externally. The metadata here is focused on the dimensions, indicators, hierarchies, measures and other data required for business analysis. of BI pages.

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The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Ontotext

The Semantic Web started in the late 90’s as a fascinating vision for a web of data, which is easy to interpret by both humans and machines. One of its pillars are ontologies that represent explicit formal conceptual models, used to describe semantically both unstructured content and databases. Take this restaurant, for example.

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Five actionable steps to GDPR compliance (Right to be forgotten) with Amazon Redshift

AWS Big Data

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It is designed for analyzing large volumes of data and performing complex queries on structured and semi-structured data. Tags provide metadata about resources at a glance.

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Event Extraction Based on Fine-Tuned Text2Event Transformer Speeds up the Fact-checking Process

Ontotext

The model and the schema Our work on automating event extraction from disinformation related content started with a review of the state-of-the-art solutions. We shortlisted several approaches and selected the Text2Event¹ model. Text2Event is a transformer model by Lu et al.² As we know, AI models are only as good as their data.