Dataconomy

APRIL 13, 2021

Data professionals have long debated the merits of the data lake versus the data warehouse. But this debate has become increasingly intense in recent times with the prevalence of data and analytics workloads in the cloud, the growing frustration with the brittleness of Hadoop, and hype around a new architectural.

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Data Lakes Data Warehouse Hadoop Analytics 237

Pickl AI

JULY 6, 2023

Here comes the role of Hive in Hadoop. Hive is a powerful data warehousing infrastructure that provides an interface for querying and analyzing large datasets stored in Hadoop. In this blog, we will explore the key aspects of Hive Hadoop. What is Hadoop ? Thus ensuring optimal performance.

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Data Science Dojo

JULY 6, 2023

Apache Hadoop: Apache Hadoop is an open-source framework for distributed storage and processing of large datasets. It provides a scalable and fault-tolerant ecosystem for big data processing. It offers pre-built connectors for a wide range of data sources, enabling data engineers to set up data pipelines quickly and easily.

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Data Engineering Data Engineer Data Engineering Data Engineering 195

Analytics Vidhya

MARCH 5, 2023

Introduction Microsoft Azure HDInsight(or Microsoft HDFS) is a cloud-based Hadoop Distributed File System version. A distributed file system runs on commodity hardware and manages massive data collections. It is a fully managed cloud-based environment for analyzing and processing enormous volumes of data.

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Analytics Vidhya

FEBRUARY 27, 2023

Introduction Enterprises here and now catalyze vast quantities of data, which can be a high-end source of business intelligence and insight when used appropriately. 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 244

Data Science Dojo

JANUARY 12, 2023

When it comes to data, there are two main types: data lakes and data warehouses. What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Which one is right for your business?

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Data Lakes Data Warehouse Hadoop Machine Learning 222

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Die Definition eines Data Lakehouse Ein Data Lakehouse ist eine moderne Datenspeicher- und -verarbeitungsarchitektur, die die Vorteile von Data Lakes und Data Warehouses vereint.

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Data Science Blog

MARCH 14, 2023

Big Data tauchte als Buzzword meiner Recherche nach erstmals um das Jahr 2011 relevant in den Medien auf. Big Data wurde zum Business-Sprech der darauffolgenden Jahre. In der Parallelwelt der ITler wurde das Tool und Ökosystem Apache Hadoop quasi mit Big Data beinahe synonym gesetzt.

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Big Data Big Data Apache Hadoop Hadoop 147

Smart Data Collective

MARCH 21, 2022

Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. Even today, there are a large number of them using data lakes to drive predictive analytics. However, the enormous rate of data growth is obstructing application scalability.

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ODSC - Open Data Science

MAY 31, 2023

Be sure to check out his talk, “ Apache Kafka for Real-Time Machine Learning Without a Data Lake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem.

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Data Lakes Machine Learning Machine Learning Apache Kafka 131

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

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ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

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Data Lakes Azure Hadoop Data Warehouse 52

Pickl AI

AUGUST 1, 2023

Key Components of Data Engineering Data Ingestion : Gathering data from various sources, such as databases, APIs, files, and streaming platforms, and bringing it into the data infrastructure. Data Processing: Performing computations, aggregations, and other data operations to generate valuable insights from the data.

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Data Engineering Data Engineer Data Engineering Data Engineering 52

The MLOps Blog

JANUARY 23, 2023

These tools may have their own versioning system, which can be difficult to integrate with a broader data version control system. For instance, our data lake could contain a variety of relational and non-relational databases, files in different formats, and data stored using different cloud providers. DVC Git LFS neptune.ai

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ML ML Data Lakes Machine Learning 52

Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis. Disruptive Trend #1: Hadoop.

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Data Lakes Hadoop Tableau Big Data 52

ODSC - Open Data Science

DECEMBER 19, 2023

Data Engineer Data engineers are responsible for the end-to-end process of collecting, storing, and processing data. They use their knowledge of data warehousing, data lakes, and big data technologies to build and maintain data pipelines.

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IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

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Data Science Analytics Analytics Data Scientist 82

Pickl AI

APRIL 6, 2023

Consequently, here is an overview of the essential requirements that you need to have to get a job as an Azure Data Engineer. In-depth knowledge of distributed systems like Hadoop and Spart, along with computing platforms like Azure and AWS. Data Warehousing concepts and knowledge should be strong.

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Azure Data Engineering Data Engineer Data Engineering 52

phData

AUGUST 9, 2023

Data volumes exploded as web, mobile, and IoT took off. ETL systems just couldn’t handle the massive flows of raw data. Open source big data tools like Hadoop were experimented with – these could land data into a repository first before transformation.

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Precisely

JANUARY 19, 2023

Organizations that can master the challenges of data integration, data quality, and context will be well positioned to identify opportunities and threats quickly, and then to take decisive action to gain competitive advantage.

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DagsHub

DECEMBER 11, 2023

However, these tools have functional gaps for more advanced data workflows. Lake File System ( LakeFS for short) is an open-source version control tool, launched in 2020, to bridge the gap between version control and those big data solutions (data lakes). This can also make the learning process challenging.

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Machine Learning Machine Learning Data Lakes Database 98

IBM Journey to AI blog

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. All phases of the data-information lifecycle.

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Flipboard

NOVEMBER 17, 2023

Prior joining AWS, as a Data/Solution Architect he implemented many projects in Big Data domain, including several data lakes in Hadoop ecosystem. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation.

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AWS Machine Learning Blog

DECEMBER 18, 2023

Prior joining AWS, as a Data/Solution Architect he implemented many projects in Big Data domain, including several data lakes in Hadoop ecosystem. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation.

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Clustering AWS Database ML 103

phData

FEBRUARY 5, 2024

Qlik Replicate Qlik Replicate is a data integration tool that supports a wide range of source and target endpoints with configuration and automation capabilities that can give your organization easy, high-performance access to the latest and most accurate data. Get to know all the ins and outs of your upcoming migration.

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SQL Database Data Quality Data Warehouse 52

Alation

FEBRUARY 20, 2020

As a cornerstone of your data architecture the EDM is a serious undertaking whether it is enabled by building on existing technologies or by deploying a single tool that includes all of the functions needed to successfully implement one. Get the latest data cataloging news and trends in your inbox.

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Data Warehouse Data Lakes Hadoop Data Preparation 52

Alation

MARCH 29, 2021

Alation helps connects to any source Alation helps connect to virtually any data source through pre-built connectors. Alation crawls and indexes data assets stored across disparate repositories, including cloud data lakes, databases, Hadoop files, and data visualization tools.

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Machine Learning Machine Learning Data Lakes Hadoop 59

Dataconomy

FEBRUARY 23, 2023

Data engineers are responsible for designing and building the systems that make it possible to store, process, and analyze large amounts of data. These systems include data pipelines, data warehouses, and data lakes, among others. However, building and maintaining these systems is not an easy task.

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Data Engineering Data Engineer Data Engineering Data Engineering 91

Alation

FEBRUARY 13, 2020

.” Part of GoDaddy’s transformation was to get the right customer data consolidated in one place and make it accessible to every employee for data-driven decision making. This meant a large Hadoop deployment, self-service analytics tools available to every employee with Tableau, and a data catalog from Alation.

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Decision Science Analytics Analytics Data Science 59

Alation

AUGUST 4, 2022

And where data was available, the ability to access and interpret it proved problematic. Big data can grow too big fast. Left unchecked, data lakes became data swamps. Some data lake implementations required expensive ‘cleansing pumps’ to make them navigable again.

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Big Data Big Data Apache Kafka Data Lakes 95

IBM Journey to AI blog

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

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phData

SEPTEMBER 20, 2023

By offering native data engineering functionality inside of Snowflake virtual warehouses, we see a thriving data ecosystem being built around Snowflake. The release of Snowpark makes our customers’ lives simpler by unifying their data lake into a complete data platform.

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SQL Python Data Lakes Machine Learning 98

IBM Journey to AI blog

SEPTEMBER 25, 2023

Uber understood that digital superiority required the capture of all their transactional data, not just a sampling. They stood up a file-based data lake alongside their analytical database. Because much of the work done on their data lake is exploratory in nature, many users want to execute untested queries on petabytes of data.

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DataRobot Blog

OCTOBER 3, 2017

This highlights the two companies’ shared vision on self-service data discovery with an emphasis on collaboration and data governance. 2) When data becomes information, many (incremental) use cases surface. Paxata booth visitors encompassed a broad range of roles, all with data responsibility in some shape or form.

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Data Lakes Azure Data Pipeline Hadoop 52