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Neo4j vs. Amazon Neptune: Graph Databases in Data Engineering

Analytics Vidhya

Introduction Managing complicated, interrelated information is more important than ever in today’s data-driven society. Traditional databases, while still valuable, often falter when it comes to handling highly connected data. Enter the unsung heroes of the data world: graph databases.

Database 213
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Reconciling The Data In Your Databases With Datafold

Data Engineering Podcast

Summary A significant portion of data workflows involve storing and processing information in database engines. In this episode Gleb Mezhanskiy, founder and CEO of Datafold, discusses the different error conditions and solutions that you need to know about to ensure the accuracy of your data. Data lakes are notoriously complex.

Database 147
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Understanding the Basics of Database Normalization

Analytics Vidhya

Introduction Data normalization is the process of building a database according to what is known as a canonical form, where the final product is a relational database with no data redundancy. More specifically, normalization involves organizing data according to attributes assigned as part of a larger data model.

Database 221
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How to Normalize Relational Databases With SQL Code?

Analytics Vidhya

Introduction Data is the new oil in this century. The database is the major element of a data science project. To generate actionable insights, the database must be centralized and organized efficiently. So, we are […] The post How to Normalize Relational Databases With SQL Code?

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Modern Data Architecture for Embedded Analytics

Every data-driven project calls for a review of your data architecture—and that includes embedded analytics. Before you add new dashboards and reports to your application, you need to evaluate your data architecture with analytics in mind. Expert guidelines for a high-performance, analytics-ready modern data architecture.

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Surveying The Market Of Database Products

Data Engineering Podcast

Summary Databases are the core of most applications, whether transactional or analytical. In recent years the selection of database products has exploded, making the critical decision of which engine(s) to use even more difficult. With Materialize, you can!

Database 189
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Designing A Non-Relational Database Engine

Data Engineering Podcast

Summary Databases come in a variety of formats for different use cases. The default association with the term "database" is relational engines, but non-relational engines are also used quite widely. Datafold has recently launched data replication testing, providing ongoing validation for source-to-target replication.

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.