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

Data Engineering Podcast

JUNE 19, 2022

Summary Metadata is the lifeblood of your data platform, providing information about what is happening in your systems. In order to level up their value a new trend of active metadata is being implemented, allowing use cases like keeping BI reports up to date, auto-scaling your warehouses, and automated data governance.

Metadata 130

Metadata MongoDB Scala MySQL 130

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

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

Data Engineering Podcast

NOVEMBER 20, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. RudderStack helps you build a customer data platform on your warehouse or data lake. What is the workflow for someone getting Sifflet integrated into their data stack?

Data Lake 130

Data Lake Data Ingestion MongoDB Scala 130

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 102

Architecture Metadata Unstructured Data Machine Learning 102

Snowflake

JUNE 4, 2024

Snowflake provides a strong data foundation anchored on unified data, optimal TCO and universal governance. The Snowflake platform eliminates silos to enable any architectural pattern, while supporting all data types and workloads.

Government 80

Government Data Ingestion Data PostgreSQL 80

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

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 88

Data Lake Business Intelligence Metadata Data Warehouse 88

Cloudera

APRIL 22, 2021

Apache Ozone is one of the major innovations introduced in CDP, which provides the next generation storage architecture for Big Data applications, where data blocks are organized in storage containers for larger scale and to handle small objects. Collects and aggregates metadata from components and present cluster state.

Pipeline-centric 101

Pipeline-centric Data Lake Hadoop Metadata 101

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. What Is a Data Mesh? It provides a more distributed, decentralized, and resilient approach to data management.

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. What Is a Data Mesh? It provides a more distributed, decentralized, and resilient approach to data management.

Government 52

Government Architecture Data Lake Data 52

Cloudera

MARCH 31, 2021

With the addition of Google Cloud, we deliver on our vision of providing a hybrid and multi-cloud architecture to support our customer’s analytics needs regardless of deployment platform. . Data Preparation (Apache Spark and Apache Hive) .

Google Cloud 94

Google Cloud Cloud Amazon Web Services Cloud Storage 94

Towards Data Science

JULY 24, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 94

Metadata Data Warehouse Data Lake Data Science 94

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Read our articles on structured vs unstructured data and unstructured data to learn more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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

ProjectPro

AUGUST 24, 2021

If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of best data engineering project examples below. With the trending advance of IoT in every facet of life, technology has enabled us to handle a large amount of data ingested with high velocity.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

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

Rockset

NOVEMBER 28, 2022

These will help users more easily configure the correct transformations on top of CDC data. The full list of templates and platforms we’re announcing support for includes the following: Template Support Debezium : An open source distributed platform for change data capture. You’ve now got a new, totally viable option.

Data Warehouse 52

Data Warehouse PostgreSQL MongoDB Data Pipeline 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

ProjectPro

NOVEMBER 15, 2021

Apache Zeppelin Source: Github Apache Zeppelin is a multi-purpose notebook that supports Data Ingestion, Data Discovery, Data Analytics , Data Visualization , and Data Collaboration. Furthermore, Cassandra is a NoSQL database in which all nodes are peers, rather than master-slave architecture.

Big Data 52

Big Data Project Metadata Programming Language 52

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. NameNode is often given a large space to contain metadata for large-scale files.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Cloudera

JUNE 4, 2018

The solution to this massive data challenge embedded the Aspire Content Processing Framework into the Cloudera Enterprise Data Hub as a Cloudera Parcel – a binary distribution format containing the program files, along with additional metadata used by Cloudera Manager.

Pharmaceutical 45

Pharmaceutical Unstructured Data Electronics Metadata 45

Snowflake

MARCH 30, 2023

3EJHjvm Once a business need is defined and a minimal viable product ( MVP ) is scoped, the data management phase begins with: Data ingestion: Data is acquired, cleansed, and curated before it is transformed. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 83

Engineering Raw Data Data Science Scala 83

ProjectPro

OCTOBER 20, 2021

AutoKeras focuses on making machine learning and deep learning more accessible with the help of Neural Architecture Search. Auto-Weka : Weka is a top-rated java-based machine learning software for data exploration. It is a function to find the best model with minimal knowledge or effort from the Data Scientist.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

ProjectPro

AUGUST 21, 2015

Data in HDFS is stored in the form of blocks and it operates on the Master-Slave Architecture. What are the steps involved in deploying a big data solution? JSON stores both data and schema together in a record and also enables complete schema evolution and splitability. This requires two separate machines.

Hadoop 40

Hadoop Big Data Metadata Java 40

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. The process requires extracting data from diverse sources, typically via APIs. Build data architecture.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Cloudera

JUNE 16, 2022

This blog aims to answer two questions as illustrated in the diagram below: How have stream processing requirements and use cases evolved as more organizations shift to “streaming first” architectures and attempt to build streaming analytics pipelines? Faster data ingestion: streaming ingestion pipelines.

Kafka 87

Kafka Manufacturing Data Lake SQL 87

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Engineering 94

Data Engineering Data Engineer Cloud Engineering 94

Monte Carlo

JULY 18, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 52

Metadata Data Warehouse Data Lake Government 52

Towards Data Science

APRIL 3, 2023

And so it almost seems unfair that new ideas are already springing up to disrupt the disruptors: Zero-ETL has data ingestion in its sights AI and Large Language Models could transform transformation Data product containers are eyeing the table’s thrown as the core building block of data Are we going to have to rebuild everything (again)?

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Monte Carlo

JULY 18, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 40

Metadata Data Warehouse Data Lake Government 40

AltexSoft

MARCH 30, 2023

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. The relatively new storage architecture powering Databricks is called a data lakehouse. Databricks lakehouse platform architecture.

Scala 64

Scala Data Lake BI Google Cloud 64

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.

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