Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Systems 87

Systems Hadoop Metadata Telecommunication 87

Monte Carlo

FEBRUARY 12, 2024

To differentiate and expand the usefulness of these models, organizations must augment them with first-party data – typically via a process called RAG (retrieval augmented generation). Today, this first-party data mostly lives in two types of data repositories.

Database 72

Database Unstructured Data Data Pipeline Metadata 72

Monte Carlo

FEBRUARY 26, 2024

A data catalog is a constantly updated inventory of the universe of data assets within an organization. It uses metadata to create a picture of the data, as well as the relationships between data assets of diverse sources, and the processing that takes place as data moves through systems.

Metadata 52

Metadata Government Data Data Governance 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

AltexSoft

AUGUST 22, 2022

So, instead of replacing or rebuilding the existing infrastructure, you add a new, ML-powered abstraction layer on top of the underlying data sources, enabling various users to access and manage the information they need without duplication. Data fabric architecture example. Unified data access. Data and metadata.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 112

IT Unstructured Data Data Architecture Government 112

ProjectPro

FEBRUARY 16, 2023

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades. This ensures that companies' data is always protected and secure.

AWS 52

AWS Data Management ETL Tools Management 52

AltexSoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Key features of a data lakehouse. Unstructured and streaming data support.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

JUNE 7, 2021

As a result, a Big Data analytics task is split up, with each machine performing its own little part in parallel. Hadoop hides away the complexities of distributed computing, offering an abstracted API to get direct access to the system’s functionality and its benefits — such as. HDFS master-slave structure. Data access options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. Specification of access conditions for specific users and groups.

Cloud 73

Cloud Data Lake Cloud Storage Metadata 73

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Monte Carlo

JULY 13, 2023

Data-driven organizations generate, collect, and store vast amounts of data. To effectively manage and analyze this data, data engineering teams must navigate a wide range of challenges, including data access, security, compliance, and data observability. Automating self-service access.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Governance 52

Snowflake

JULY 10, 2023

With this new Snowpark capability, data engineers and data scientists can process any type of file directly in Snowflake, regardless if files are stored in Snowflake-managed storage or externally. Mike Tuck, Air Pollution Specialist Why unstructured data?

Unstructured Data 40

Unstructured Data Python Process Scala 40

Snowflake

MARCH 30, 2023

Automation , because the same loader patterns are used for both and the same metadata tags are expected from both, meaning the applied date timestamp in the business vault will match up with the raw date timestamp where it came from. These methods can be applied to structured and semi-structured data as well.

Engineering 84

Engineering Raw Data Data Science Machine Learning 84

Data Engineering Podcast

FEBRUARY 3, 2019

So I decided to focus my energies in research data management. Open Context is an open access data publishing service for archaeology. It started because we need better ways of dissminating structured data and digital media than is possible with conventional articles, books and reports.

Digital Media 100

Digital Media Media PostgreSQL Datasets 100

Zalando Engineering

JANUARY 30, 2023

This structure allows all stakeholders involved in incident response to clearly understand the executed actions and target state of the system to expect. Lastly, by having playbooks in a single location, our Incident Responders and Incident Commanders have easy access to all available emergency procedures in a consistent format.

Management 55

Management Metadata Software Engineering Software Engineer 55

Towards Data Science

MARCH 5, 2024

The storage system is using Capacitor, a proprietary columnar storage format by Google for semi-structured data and the file system underneath is Colossus, the distributed file system by Google. Choosing the right model depends on your data access patterns and compression capabilities. So, which model should you choose?

Bytes 69

Bytes Google Cloud Cloud Storage Utilities 69

Cloudera

SEPTEMBER 17, 2020

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. . Our solution: Cloudera Data Visualization.

Data Warehouse 81

Data Warehouse Unstructured Data Pharmaceutical MySQL 81

Monte Carlo

APRIL 1, 2021

Over the past few years, data lakes have emerged as a must-have for the modern data stack. But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind. Who has access to it?

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Netflix Tech

MARCH 5, 2019

Challenges & Opportunities in the Infra Data Space Security Events Platform for Anomaly Detection How can we develop a complex event processing system to ingest semi-structured data predicated on schema contracts from hundreds of sources and transform it into event streams of structured data for downstream analysis?

Cloud 73

Cloud Building Amazon Web Services Metadata 73

ProjectPro

JANUARY 31, 2023

Data Variety Hadoop stores structured, semi-structured and unstructured data. RDBMS stores structured data. Data storage Hadoop stores large data sets. RDBMS stores the average amount of data. Works with only structured data. Hardware Hadoop uses commodity hardware.

Big Data 52

Big Data Hadoop Relational Database AWS 52

RandomTrees

SEPTEMBER 6, 2020

A combination of structured and semi structured data can be used for analysis and loaded into the cloud database without the need of transforming into a fixed relational scheme first. This stage handles all the aspects of data storage like organization, file size, structure, compression, metadata, statistics.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Netflix Tech

DECEMBER 14, 2018

A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve. NMDB is built to be a highly scalable, multi-tenant, media metadata system that can serve a high volume of write/read throughput as well as support near real-time queries.

Media 96

Media Database Metadata Data Schemas 96

Cloudera

MAY 17, 2021

Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform. Beyond there being a number of choices each with very different strengths, the parameters for your decision have also changed.

Data Warehouse 90

Data Warehouse Cloud Government Metadata 90

Ascend.io

JULY 19, 2023

Implementing Data Governance Effective data governance is the backbone of any data management strategy, and even more so for a decentralized approach like data mesh. A robust data governance framework is crucial to ensure data quality, manage data access, and maintain compliance with regulatory requirements.

Data Governance 40

Data Governance Government Metadata Data 40

AltexSoft

JUNE 26, 2023

Commonly, the entire flow is fully automated and consists of three main steps — data extraction, transformation, and loading ( ETL or ELT , for short, depending on the order of the operations.) Dive deeper into the subject by reading our article Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

JANUARY 24, 2023

You can leverage AWS Glue to discover, transform, and prepare your data for analytics. In addition to databases running on AWS, Glue can automatically find structured and semi-structured data kept in your data lake on Amazon S3, data warehouse on Amazon Redshift, and other storage locations.

AWS 52

AWS ETL Tools Data Lake Scala 52

AltexSoft

SEPTEMBER 23, 2021

It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. With a data hub, businesses receive the means to structure, and harmonize information collected from various sources. A data hub serves as a gateway to dispense the required data.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Hepta Analytics

FEBRUARY 14, 2022

The purpose of the data is not determined. The data is easily accessible and is easy to update. The data is in use and is difficult to update. Airflow installation has the following components: Scheduler – triggers the scheduled workflow and submits tasks to be done Executor – runs tasks.

Data Ingestion 52

Data Ingestion Data Engineer Data Engineering Engineering 52

ProjectPro

JANUARY 31, 2022

Snowflake also has data discovery features, allowing users to find and retrieve data more efficiently and rapidly. Snowflake Data Marketplace gives users rapid access to various third-party data sources. Moreover, numerous sources offer unique third-party data that is instantly accessible when needed.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

AltexSoft

JULY 29, 2022

How HDFS master-slave structure works. A master node called NameNode maintains metadata with critical information, controls user access to the data blocks, makes decisions on replications, and manages slaves. Today, companies have the opportunity to run Big Data analytics on Hadoop without investing in hardware.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

NOVEMBER 15, 2021

When any particular project is open-sourced, it makes the source code accessible to anyone. The adaptability and technical superiority of such open-source big data projects make them stand out for community use. DataFrames are used by Spark SQL to accommodate structured and semi-structured data.

Big Data 52

Big Data Project Metadata Programming Language 52

Ascend.io

AUGUST 31, 2023

The Data Lake Pattern Emerging in contrast to the structured world of warehousing, data lakes cater to the dynamic and diverse nature of modern internet-based applications. These fluid conditions require unstructured data environments that natively operate with constantly changing formats, data structures, and data semantics.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Knowledge Hut

DECEMBER 21, 2023

Features: HDFS incorporates concepts like blocks, data nodes, node names, etc. The files stored in HDFS are easily accessible. The data to be stored is distributed over multiple machines. Avro creates binary data which can be both compressed as well as split. Pros: Avro stores data in a compact and efficient manner.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52