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11 Open-Source Data Engineering Tools Every Pro Should Use

ODSC - Open Data Science

This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time. Looker Looker, a cloud-based business intelligence platform, focuses on data exploration and analysis.

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Top 5 Tools for Building an Interactive Analytics App

Smart Data Collective

An interactive analytics application gives users the ability to run complex queries across complex data landscapes in real-time: thus, the basis of its appeal. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights. Amazon Redshift is a fast and widely used data warehouse.

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Visionary Data Quality Paves the Way to Data Integrity

Precisely

And the desire to leverage those technologies for analytics, machine learning, or business intelligence (BI) has grown exponentially as well. Instead of moving customer data to the processing engine, we move the processing engine to the data. Simply design data pipelines, point them to the cloud environment, and execute.

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How Cloud Data Platforms improve Shopfloor Management

Data Science Blog

The fusion of data in a central platform enables smooth analysis to optimize processes and increase business efficiency in the world of Industry 4.0 using methods from business intelligence , process mining and data science. Are you interested in scalable data architectures for your shopfloor management ?

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Discover the Snowflake Architecture With All its Pros and Cons- NIX United

Mlearning.ai

Today, companies are facing a continual need to store tremendous volumes of data. The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. Data warehousing is a vital constituent of any business intelligence operation.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

We also discuss different types of ETL pipelines for ML use cases and provide real-world examples of their use to help data engineers choose the right one. What is an ETL data pipeline in ML? Xoriant It is common to use ETL data pipeline and data pipeline interchangeably.

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How Databricks and Tableau customers are fueling innovation with data lakehouse architecture

Tableau

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

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