Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

Cloudera

DECEMBER 12, 2018

I would like to start off by asking you to tell us about your background and what kicked off your 20-year career in relational database technology? Greg Rahn: I first got introduced to SQL relational database systems while I was in undergrad. The one that people will use for data warehousing includes Apache Impala in it.

Data Warehouse 42

Data Warehouse Relational Database Hadoop Database 42

DareData

JANUARY 30, 2023

In this post, we'll discuss some key data engineering concepts that data scientists should be familiar with, in order to be more effective in their roles. These concepts include concepts like data pipelines, data storage and retrieval, data orchestrators or infrastructure-as-code.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Monte Carlo

MAY 28, 2024

Data Transformation : Clean, format, and convert extracted data to ensure consistency and usability for both batch and real-time processing. Data Loading : Load transformed data into the target system, such as a data warehouse or data lake. Used for identifying and cataloging data sources.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

phData: Data Engineering

SEPTEMBER 19, 2023

This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake? What are Data Modeling Methodologies, and Why Are They Important for a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Precisely

JANUARY 25, 2024

Today’s cloud systems excel at high-volume data storage, powerful analytics, AI, and software & systems development. Cloud-based DevOps provides a modern, agile environment for developing and maintaining applications and services that interact with the organization’s mainframe data.

Metadata 69

Metadata Relational Database Data Governance Government 69

AltexSoft

AUGUST 4, 2021

Now let’s think of sweets as the data required for your company’s daily operations. Instead of combing through the vast amounts of all organizational data stored in a data warehouse, you can use a data mart — a repository that makes specific pieces of data available quickly to any given business unit.

Data Lake 64

Data Lake Data Warehouse ETL Tools Database 64

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. As a certified Azure Data Engineer, you have the skills and expertise to design, implement and manage complex data storage and processing solutions on the Azure cloud platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Cloudera

SEPTEMBER 9, 2021

Cloudera Machine Learning or Cloudera Data Warehouse), to deliver fast data and analytics to downstream components. When it comes to storage, COD takes advantage of cloud-native capabilities for data storage by: Using cloud object storage (e.g.,

Database 95

Database AWS Relational Database Cloud 95

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. And most of this data has to be handled in real-time or near real-time.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

FEBRUARY 8, 2023

It offers users a data integration tool that organizes data from many sources, formats it, and stores it in a single repository, such as data lakes, data warehouses, etc., Glue uses ETL jobs for extracting data from various AWS cloud services and integrating it into data warehouses and lakes.

AWS 98

AWS Scala Metadata Data Lake 98

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

NOVEMBER 17, 2023

Understanding SQL You must be able to write and optimize SQL queries because you will be dealing with enormous datasets as an Azure Data Engineer. To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. But they should!

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. But they should!

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Edureka

FEBRUARY 9, 2023

Here are some role-specific skills to consider if you want to become an Azure data engineer: Programming languages are used in the majority of data storage and processing systems. Data engineers must be well-versed in programming languages such as Python, Java, and Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

Silectis

JANUARY 3, 2021

Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse. Cassandra A database built by the Apache Foundation. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

NOVEMBER 19, 2023

As a result, data engineers working with big data today require a basic grasp of cloud computing platforms and tools. Businesses can employ internal, public, or hybrid clouds depending on their data storage needs, including AWS, Azure, GCP, and other well-known cloud computing platforms.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

Knowledge Hut

JULY 24, 2023

It allows changes to be made at various levels of a database system without causing disruptions or requiring extensive modifications to the applications that rely on the data. What is Data Independence of DBMS? It tells us about logical relationships between the data elements and entities in the database.

Database Design 52

Database Design Relational Database Database Metadata 52

Knowledge Hut

NOVEMBER 28, 2023

ETL is central to getting your data where you need it. Relational database management systems (RDBMS) remain the key to data discovery and reporting, regardless of their location. These pipelines help you configure storage that can change the data engineer skills and tools required for ETL/ELT injection.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

ProjectPro

JANUARY 19, 2022

Here are some role-specific skills you should consider to become an Azure data engineer- Most data storage and processing systems use programming languages. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Different methods are used to store different types of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

AltexSoft

SEPTEMBER 10, 2021

What is data integration and why is it important? Data integration is the process of taking data from multiple disparate internal and external sources and putting it in a single location (e.g., data warehouse ) to achieve a unified view of collected data. Key types of data integration.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

ProjectPro

APRIL 1, 2016

GlobeNewsWire.com Cloudera – the global provider of the easiest and the most secure data management to be built of Apache Hadoop , recently announced that recently it has moved from the Challengers to the Visionaries position in the 2016 Gartner Magic Quadrant for Data Warehouse and Data Management solution for analytics.

Hadoop 52

Hadoop BI Big Data Big Data Tools 52

Knowledge Hut

NOVEMBER 17, 2023

Azure Storage As the name suggests, Azure storage deals with data storage solutions on the Microsoft cloud. It is highly secure and scalable and can be used to store a variety of data objects. They can also use Azure CLI or Azure PowerShell for configuring tasks and data management.

Data Lake 52

Data Lake Programming Language Certification Java 52

Grouparoo

NOVEMBER 29, 2021

The structure of databases tends to depend on each vendor's proprietary implementation, though for data processing, the database's internal structure typically has a limited impact on processing functions. When doing Reverse ETL with Grouparoo, data sources are most commonly data warehouses.

Raw Data 40

Raw Data Big Data Relational Database Data Warehouse 40

Knowledge Hut

JUNE 23, 2023

You should be thorough with technicalities related to relational and non-relational databases, Data security, ETL (extract, transform, and load) systems, Data storage, automation and scripting, big data tools, and machine learning.

Data Engineering 52

Data Engineering Data Engineer Engineering NoSQL 52

Cloud Academy

JANUARY 27, 2022

These fundamentals will give you a solid foundation in data and datasets. Knowing SQL means you are familiar with the different relational databases available, their functions, and the syntax they use. Have knowledge of regular expressions (RegEx) It is essential to be able to use regular expressions to manipulate data.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Ascend.io

JANUARY 2, 2024

Ingestion Points at the Source The journey of a data pipeline begins at its sources – or more technically, at the ingestion points. These are the interfaces where the pipeline taps into various systems to acquire data. Actions: Identify the primary goals of your pipeline, such as automating data reporting for monthly sales data.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

AltexSoft

JUNE 26, 2023

Find sources of relevant data. Choose data collection methods and tools. Decide on a sufficient data amount. Set up data storage technology. Below, we’ll elaborate on each step one by one and share our experience of data collection. The difference between data warehouses, lakes, and marts.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

OCTOBER 3, 2023

Additionally, for a job in data engineering, candidates should have actual experience with distributed systems, data pipelines, and related database concepts. Students have the chance to put Azure data solutions into practice with the Microsoft Azure DP-203 certification training.

Data Engineering 52

Data Engineering Data Engineer Engineering Cloud Computing 52

Knowledge Hut

DECEMBER 26, 2023

Database-centric In bigger organizations, Data engineers mainly focus on data analytics since the data flow in such organizations is huge. Data engineers who focus on databases work with data warehouses and develop different table schemas. What are the responsibilities of a Data Engineer?

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

Knowledge Hut

MARCH 20, 2024

They are responsible for establishing and managing data pipelines that make it easier to gather, process, and store large volumes of structured and unstructured data. Assembles, processes, and stores data via data pipelines that are created and maintained.

Software Engineer 52

Software Engineer Software Engineering Engineering Java 52

ProjectPro

JANUARY 31, 2023

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

Big Data 52

Big Data Hadoop Relational Database AWS 52

ProjectPro

NOVEMBER 15, 2021

DataFrames are used by Spark SQL to accommodate structured and semi-structured data. You can also access data through non-relational databases such as Apache Cassandra, Apache HBase, Apache Hive, and others like the Hadoop Distributed File System. Calcite has chosen to stay out of the data storage and processing business.

Big Data 52

Big Data Project Metadata Programming Language 52