Analytics Vidhya

FEBRUARY 27, 2023

Delta Lake is an open-source warehouse layer designed to run on top of data lakes analogous to […] The post A Comprehensive Guide on Delta Lake appeared first on Analytics Vidhya. Delta Lake allows businesses to access and break new data down in real time.

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Data Lakes Business Intelligence Business Intelligence Analytics 245

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. Understanding the ETL Process. Before you understand what is ETL tool , you need to understand the ETL Process first. Types of ETL Tools.

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Pickl AI

APRIL 6, 2023

Data Engineering is one of the most productive job roles today because it imbibes both the skills required for software engineering and programming and advanced analytics needed by Data Scientists. In-depth knowledge of distributed systems like Hadoop and Spart, along with computing platforms like Azure and AWS. What is Polybase?

Azure 52

Azure Data Engineering Data Engineer Data Engineering 52

ODSC - Open Data Science

SEPTEMBER 27, 2023

Cost-Efficiency By leveraging cost-effective storage solutions like the Hadoop Distributed File System (HDFS) or cloud-based storage, data lakes can handle large-scale data without incurring prohibitive costs. They are optimized for complex analytical queries and reporting.

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Data Lakes Data Warehouse Database Big Data 98

Becoming Human

JANUARY 23, 2023

Now, Big Data technologies mostly focus on things like Data Mining , Data Warehousing , Preprocessing Data , and Storing the Data , and Data Science technologies are more towards the Analytical part.

Data Science 105

Data Science Big Data Big Data Deep Learning 105

Mlearning.ai

MAY 16, 2023

ETL Design Pattern The ETL (Extract, Transform, Load) design pattern is a commonly used pattern in data engineering. ETL Design Pattern Here is an example of how the ETL design pattern can be used in a real-world scenario: A healthcare organization wants to analyze patient data to improve patient outcomes and operational efficiency.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

NOVEMBER 15, 2023

Importance of Data Lakes Data Lakes play a pivotal role in modern data analytics, providing a platform for Data Scientists and analysts to extract valuable insights from diverse data sources. It involves the extraction, transformation, and loading (ETL) process to organize data for business intelligence purposes.

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Data Lakes Data Warehouse Database ETL 52

The MLOps Blog

JANUARY 23, 2023

With lakeFS it is possible to test ETLs on top of production data, in isolation, without copying anything. Also, lakeFS can be used for data management, ETL testing, reproducibility for experiments, and CI/CD for data to prevent future failures. This makes it easier to build robust data pipelines and do more complex data analytics.

ML 52

ML ML Data Lakes Machine Learning 52

IBM Journey to AI blog

JANUARY 18, 2023

While traditional data warehouses made use of an Extract-Transform-Load (ETL) process to ingest data, data lakes instead rely on an Extract-Load-Transform (ELT) process. This adds an additional ETL step, making the data even more stale. One node of the fabric may provide raw data to another that, in turn, performs analytics.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

phData

FEBRUARY 5, 2024

Matillion Matillion is a complete ETL tool that integrates with an extensive list of pre-built data source connectors, loads data into cloud data environments such as Snowflake, and then performs transformations to make data consumable by analytics tools such as Tableau and PowerBI. We have you covered !

SQL 52

SQL Database Data Quality Data Warehouse 52

Dataconomy

FEBRUARY 23, 2023

This involves working with various tools and technologies, such as ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes, to move data from its source to its destination. Cloud providers offer various services such as storage, compute, and analytics, which can be used to build and operate big data systems.

Data Engineering 91

Data Engineering Data Engineer Data Engineering Data Engineering 91

Alation

JANUARY 25, 2022

A data fabric utilizes continuous analytics over existing, discoverable, and inferred metadata assets to support the design, deployment, and utilization of integrated and reusable data across all environments, including hybrid and multi-cloud platforms.” See Gartner’s “ How DataOps Amplifies Data and Analytics Business Value ”).

DataOps 52

DataOps SQL ML ML 52

Alation

FEBRUARY 20, 2020

Business Intelligence used to require months of effort from BI and ETL teams. More recently, we’ve seen Extract, Transform and Load (ETL) tools like Informatica and IBM Datastage disrupted by self-service data preparation tools. You used to be able to get those standards from your colleague in the BI/ETL team.

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ETL Hadoop Tableau Business Intelligence 52

Alation

FEBRUARY 20, 2020

With the year coming to a close, many look back at the headlines that made major waves in technology and big data – from Spark to Hadoop to trends in data science – the list could go on and on. However, most are only deployed over one data store (Hadoop or other various backends). Reports will be just the beginning.

Data Warehouse 52

Data Warehouse Hadoop ETL Data Science 52

IBM Journey to AI blog

SEPTEMBER 25, 2023

But what most people don’t realize is that behind the scenes, Uber is not just a transportation service; it’s a data and analytics powerhouse. This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success.

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