Silectis

JANUARY 3, 2021

Big Query Google’s cloud data warehouse. Data Architecture Data architecture is a composition of models, rules, and standards for all data systems and interactions between them. Data Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

NOVEMBER 28, 2023

As a data engineer description, you must be ready to explore large-scale data processing and use your expertise and soft skills to ensure a scalable and reliable working environment. Data engineers need to work with large amounts of data and maintain the architectures used in various data science projects.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

SEPTEMBER 29, 2023

By combining data from various structured and unstructured data systems into structures, Microsoft Azure Data Engineers will be able to create analytics solutions. Why Should You Get an Azure Data Engineer Certification? You can browse the data lake files with the interactive training material.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

AUGUST 25, 2023

Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. Let’s dive in.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 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

Towards Data Science

FEBRUARY 15, 2023

Concepts, theory, and functionalities of this modern data storage framework Photo by Nick Fewings on Unsplash Introduction I think it’s now perfectly clear to everybody the value data can have. To use a hyped example, models like ChatGPT could only be built on a huge mountain of data, produced and collected over years.

Data Lake 74

Data Lake Data Warehouse Hadoop Data Architecture 74

ProjectPro

JANUARY 31, 2022

This blog walks you through what does Snowflake do , the various features it offers, the Snowflake architecture, and so much more. Table of Contents Snowflake Overview and Architecture What is Snowflake Data Warehouse? Snowflake is not based on existing database systems or big data software platforms like Hadoop.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Snowflake

JANUARY 22, 2024

In 2020, Fidelity kicked off its digital transformation and established an Enterprise Data Lake (EDL) along with Data Labs. All of Fidelity’s storage abides by its data security framework and data governance policies, and provides a holistic approach to metadata management.

Engineering 63

Engineering Data Lake Unstructured Data Metadata 63

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). Tables are governed as per agreed upon company standards.

Big Data 78

Big Data Data Management Management Metadata 78

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

ProjectPro

FEBRUARY 8, 2023

Let us dive deeper into this data integration solution by AWS and understand how and why big data professionals leverage it in their data engineering projects. It offers a simple and efficient solution for data processing in organizations. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog.

AWS 98

AWS Scala Metadata Data Lake 98

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance. Architecture overview. Separate storage.

IT 93

IT Data Lake Data Warehouse Cloud Storage 93

Monte Carlo

JANUARY 25, 2023

When it comes to the question of building or buying your data stack, there’s never a one-size-fits-all solution for every data team—or every component of your data stack. Data storage and compute are very much the foundation of your data platform. Let’s jump in!

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

OCTOBER 30, 2021

Data engineer’s responsibilities — Development and Architecture. Data engineer’s integral task is building and maintaining data infrastructure — the system managing the flow of data from its source to destination. Engineers can build different types of architectures by mixing and matching these parts.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

LinkedIn Engineering

JULY 27, 2023

The landing page lists all the resource recommendations along with metadata around resource owners (Azure security groups), recommendation message, current lifecycle status of the recommendation, due date, assigned engineer, last action message in terms of comments, and a history modal option to check the timeline of actions taken.

Metadata 75

Metadata Utilities Cloud Data Lake 75

Big Data Tools

SEPTEMBER 6, 2021

There are also several changes in KRaft (namely Revise KRaft Metadata Records and Producer ID generation in KRaft mode ), along with many other changes. Unfortunately, the feature that was most awaited (at least by me) – tiered storage – has been postponed for a subsequent release. Support for Scala 2.12 And more files means more time.

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 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

Big Data Tools

SEPTEMBER 6, 2021

There are also several changes in KRaft (namely Revise KRaft Metadata Records and Producer ID generation in KRaft mode ), along with many other changes. Unfortunately, the feature that was most awaited (at least by me) – tiered storage – has been postponed for a subsequent release. Support for Scala 2.12 And more files means more time.

Data Engineering 40

Data Engineering Data Engineer Engineering Big Data Tools 40

ProjectPro

NOVEMBER 15, 2021

It was built from the ground up for interactive analytics and can scale to the size of Facebook while approaching the speed of commercial data warehouses. Presto allows you to query data stored in Hive, Cassandra, relational databases, and even bespoke data storage. To contribute to this project, hop onto: [link] 19.DataHub

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

FEBRUARY 8, 2017

In 2017, big data platforms that are just built only for hadoop will fail to continue and the ones that are data and source agnostic will survive. Organizations are embarking on data lake strategy for applications that are centralized and for applications coming together on a single central platform.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Variety Hadoop stores structured, semi-structured and unstructured data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

NOVEMBER 30, 2021

In extract-transform-load (ETL), data is obtained from multiple sources, transformed, and stored in a single data warehouse, with access to data analysts , data scientists , and business analysts for data visualization and statistical analysis model building, forecasting, etc.

Process 52

Process Data Pipeline Data Warehouse AWS 52

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 44

Big Data NoSQL Data Lake Hadoop 44

Snowflake

MARCH 30, 2023

Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse? Snowflake can also ingest external tables from on-premise s data sources via S3-compliant data storage APIs. The friction of data movement is reduced. Yes, feature stores are part of the MLOps discipline.

Engineering 83

Engineering Raw Data Data Science Scala 83

Monte Carlo

SEPTEMBER 16, 2020

While our ability to collect, store, aggregate, and visualize this data has largely kept up with the needs of modern data teams (think: domain-oriented data meshes , cloud warehouses , data visualization tools , and data modeling solutions ), the mechanics behind data quality and data integrity has lagged.

Software Engineer 52

Software Engineer Software Engineering Data Data Pipeline 52

ProjectPro

DECEMBER 10, 2021

The service provider's data center hosts the underlying infrastructure, software, and app data. Azure Redis Cache is an in-memory data storage, or cache system, based on Redis that boosts the flexibility and efficiency of applications that rely significantly on backend data stores. Explain Azure Redis Cache.

BI 52

BI Cloud Computing SQL Database 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. For example, developers can use Twitter API to access and collect public tweets, user profiles, and other data from the Twitter platform.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

AUGUST 21, 2015

Hadoop Framework works on the following two core components- 1)HDFS – Hadoop Distributed File System is the java based file system for scalable and reliable storage of large datasets. Data in HDFS is stored in the form of blocks and it operates on the Master-Slave Architecture. This data needs to be stored in HDFS.

Hadoop 40

Hadoop Big Data Metadata Java 40

Towards Data Science

APRIL 3, 2023

It’s important to note the data is still in a relatively raw state. At the moment, this tight integration is possible because most zero-ETL architectures require both the transactional database and data warehouse to be from the same cloud provider. No duplicate data storage. Pros : Reduced latency.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Monte Carlo

JANUARY 12, 2024

On the data lake side, Databricks has launched Unity Catalog to help bring more metadata, structure, and governance to data assets. Real-time data/insights Being able to access real-time data for analysis might sound like overkill to some, but that’s just no longer the case.

Big Data 59

Big Data Data Analytics Data Science Data Lake 59

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? Data-first companies have embraced data platforms as an effective way to aggregate, operationalize, and democratize data at scale across the organization. Data Storage and Processing The first layer? Image courtesy of Monte Carlo.

Building 52

Building BI Data Lake Data Governance 52

AltexSoft

MARCH 14, 2023

Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. What is a modern data stack? A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it. Modern data stack architecture.

IT 59

IT Data Warehouse Data Governance Data Lake 59

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. What is a data mesh?

IT 45

IT Data Lake Business Intelligence Data Architecture 45