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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. Key Differences.

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Top 5 Tools for Building an Interactive Analytics App

Smart Data Collective

The application presents a massive volume of unstructured data through a graphical or programming interface using the analytical abilities of business intelligence technology to provide instant insight. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights.

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Business Intelligence Technologies: Definitive Guide

FineReport

Therefore, the technical requirements for analyzing data are constantly increasing. This article will systematically introduce the definition of BI technology, the technology list and provide technology examples and tool recommendations. Data warehouse. Data querying & discovery. BI Technology Meaning.

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Data migration to Snowflake, a comprehensive primer

Octopai

Data migration can be a daunting task, especially when dealing with large volumes of data. Snowflake is one of the leading cloud-based data warehouse that provides scalability, flexibility, and ease of use. Snowflake data warehouse platform has been designed to leverage the power of modern-day cloud computing technology.

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Business Intelligence vs Data Science vs Data Analytics

FineReport

If you are curious about the difference and similarities between them, this article will unveil the mystery of business intelligence vs. data science vs. data analytics. Definition: BI vs Data Science vs Data Analytics. What is Data Science? Photo by Chris Ried on Unsplash. What is Business Intelligence?

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Ontotext Knowledge Graph Platform: The Modern Way of Building Smart Enterprise Applications

Ontotext

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. The first challenge here is how to enable agile enterprise information management.

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Big Data Sets New Standards In Stream Processing For Emerging Markets

Smart Data Collective

This is where real-time stream processing enters the picture, and it may probably change everything you know about big data. Read this article as we’ll tackle what big data and stream processing are. We’ll also deal with how big data stream processing can help new emerging markets in the world. What is Big Data?