Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake. What is a data fabric?

Data Lake 81

Data Lake Analytics Application Cloud Storage Architecture 81

ProjectPro

JULY 22, 2016

For the same cost, organizations can now store 50 times as much data as in a Hadoop data lake than in a data warehouse. Data lake is gaining momentum across various organizations and everyone wants to know how to implement a data lake and why.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

Databand.ai

AUGUST 30, 2023

A DataOps architecture is the structural foundation that supports the implementation of DataOps principles within an organization. It encompasses the systems, tools, and processes that enable businesses to manage their data more efficiently and effectively. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems. What Is ELT? So, what exactly is ELT?

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

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

phData: Data Engineering

SEPTEMBER 27, 2024

It enables advanced analytics, makes debugging your marketing automations easier, provides natural audit trails for compliance, and allows for flexible, evolving customer data models. So next time you’re designing your customer data architecture in your CDP, don’t just think about the current state of your customers.

Data 52

Data Raw Data Data Lake Architecture 52

Knowledge Hut

APRIL 25, 2024

They simplify data processing for our brains and give readers a quick overview of past, present, and future performance by helping the user to visualize otherwise complex and weighty raw data. By providing data solutions to departments that need them and to individuals with an insatiable curiosity for data, BI is made scalable.

Business Intelligence 52

Business Intelligence BI Raw Data Data Lake 52

Monte Carlo

AUGUST 31, 2023

Data pipelines can handle both batch and streaming data, and at a high-level, the methods for measuring data quality for either type of asset are much the same. In many ways, the cloud makes data easier to manage, more accessible to a wider variety of users, and far faster to process.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Monte Carlo

JUNE 14, 2023

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses. Zero ETL is a bit of a misnomer.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Rockset

JANUARY 31, 2023

SkyHive platform Challenges with MongoDB for Analytical Queries 16 TB of raw text data from our web crawlers and other data feeds is dumped daily into our S3 data lake. That data was processed and then loaded into our analytics and serving database, MongoDB.

MongoDB 59

MongoDB Pharmaceutical Recruitment Raw Data 59

Knowledge Hut

OCTOBER 30, 2023

The role of a Power BI developer is extremely imperative as a data professional who uses raw data and transforms it into invaluable business insights and reports using Microsoft’s Power BI. Develop a long-term vision for Power BI implementation and data analytics. Who is a Power BI Developer?

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Data Engineering Weekly

JANUARY 15, 2023

[link] Piethein Strengholt: Medallion architecture - best practices for managing Bronze, Silver, and Gold I always find myself very uncomfortable with the naming convention of medallion data architecture. The author writes a few best practices for managing medallion-style architecture.

Data Engineer 52

Data Engineer Data Engineering Engineering Metadata 52

Knowledge Hut

JUNE 30, 2023

The practice of designing, building, and maintaining the infrastructure and systems required to collect, process, store, and deliver data to various organizational stakeholders is known as data engineering. You can pace your learning by joining data engineering courses such as the Bootcamp Data Engineer.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

ProjectPro

JUNE 9, 2021

Data Science- Definition Data Science is an interdisciplinary branch encompassing data engineering and many other fields. Data Science involves applying statistical techniques to raw data, just like data analysts, with the additional goal of building business solutions.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

Rockset

JANUARY 28, 2020

Testing new functionality on their transactional data store is costly and can impact production. Ad hoc queries to measure the accuracy of the checkout process in real time are not possible with traditional data architectures. When in the experimental phase, quick schema changes are required when analyzing their data.

Retail 40

Retail Google Cloud Raw Data Data Lake 40

Knowledge Hut

NOVEMBER 28, 2023

Technical Data Engineer Skills 1.Python Python Python is one of the most looked upon and popular programming languages, using which data engineers can create integrations, data pipelines, integrations, automation, and data cleansing and analysis.

Data Engineer 52

Data Engineer Data Engineering Engineering Generalist 52

Rockset

FEBRUARY 6, 2019

Aggregator Leaf Tailer (ALT) is the data architecture favored by web-scale companies, like Facebook, LinkedIn, and Google, for its efficiency and scalability. In this blog post, I will describe the Aggregator Leaf Tailer architecture and its advantages for low-latency data processing and analytics.

Lambda Architecture 40

Lambda Architecture Architecture MongoDB Kafka 40

ProjectPro

JULY 27, 2021

Data engineers and data scientists work very closely together, but there are some differences in their roles and responsibilities. Data Engineer Data scientist The primary role is to design and implement highly maintainable database management systems. It is difficult to query the required unstructured data.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

JANUARY 31, 2022

It also offers a unique architecture that allows users to quickly build tables and begin querying data without administrative or DBA involvement. Snowflake is a cloud-based data platform that provides excellent manageability regarding data warehousing, data lakes, data analytics, etc.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

JANUARY 31, 2023

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 52

Big Data Hadoop Relational Database AWS 52

ProjectPro

NOVEMBER 14, 2015

This data can be analysed using big data analytics to maximise revenue and profits. Big data technologies used: Microsoft Azure, Azure Data Factory, Azure Databricks, Spark Big Data Architecture: This sample Hadoop real-time project starts off by creating a resource group in azure.

Hadoop 52

Hadoop Project Big Data Healthcare 52

AltexSoft

MAY 12, 2023

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. There are several widely used unstructured data storage solutions such as data lakes (e.g., Build data architecture.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

FEBRUARY 16, 2023

Your SQL skills as a data engineer are crucial for data modeling and analytics tasks. Making data accessible for querying is a common task for data engineers. Collecting the raw data, cleaning it, modeling it, and letting their end users access the clean data are all part of this process.

Data Engineer 52

Data Engineer Data Engineering SQL Engineering 52

The Modern Data Company

MARCH 1, 2024

For today’s Chief Data Officers (CDOs) and data teams, the struggle is real. We’re drowning in data yet thirsting for actionable insights. We need a new approach, a paradigm shift that delivers data with the agility and efficiency of a speedboat – enter Data Products.

Database-centric 40

Database-centric Data Lake Government Retail 40

Towards Data Science

APRIL 3, 2023

Zero-ETL What it is : A misnomer for one thing; the data pipeline still exists. Today, data is often generated by a service and written into a transactional database. An automatic pipeline is deployed which not only moves the raw data to the analytical data warehouse, but modifies it slightly along the way.

Data Engineer 98

Data Engineer Data Engineering Engineering Data Warehouse 98

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64

Monte Carlo

APRIL 4, 2023

For example, Snowflake offers data warehouses in different sizes and organizations may have several “data warehouses” to support different data use cases. A data mesh might leverage one or several cloud data warehouses depending on how closely the organization adheres to the dogma.

Data Warehouse 52

Data Warehouse Data Governance Data Architecture 52

Monte Carlo

JULY 30, 2020

In the age of self-service business intelligence , nearly every company considers themselves a data-first company, but not every company is treating their data architecture with the level of democratization and scalability it deserves. Your company, for one, views data as a driver of innovation. You will not regret it).

IT 45

IT Data Lake Architecture Data Architecture 45