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

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

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 68

Cloud Data Lake Cloud Storage Metadata 68

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

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.

Unstructured Data 80

Unstructured Data Pharmaceutical Data Warehouse MySQL 80

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

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

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 Data Lake ETL Tools Scala 52

Towards Data Science

JANUARY 17, 2024

These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction. They are designed to handle the challenges of big data like size, speed, and structure. Data engineers often face a plethora of choices.

Big Data 72

Big Data Data Data Storage SQL 72

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 Engineering Data Engineer Engineering 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

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

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

Striim

JANUARY 4, 2023

When your applications access data from each other, it can cause high coupling, i.e., applications are highly interdependent on each other. If you make any changes in the data structure, such as dropping a table from the database, it can affect the applications that are ingesting or using data from it.

PostgreSQL 52

PostgreSQL Data Warehouse Data Lake Data 52

Silectis

JANUARY 3, 2021

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. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Rockset

JANUARY 28, 2020

Aside from video data from each camera-equipped store, Standard deals with other data sets such as transactional data, store inventory data that arrive in different formats from different retailers, and metadata derived from the extensive video captured by their cameras.

Retail 40

Retail Google Cloud Raw Data Data Lake 40

Monte Carlo

JULY 10, 2023

Accuracy reflects the degree to which the data correctly describes the “real-world” objects being described. For example, let’s say a streaming provider has 10 million overall subscribers who can access its content. According to the CRM’s data set, the streaming provider has 13 million subscribers.

Data Collection 40

Data Collection Data Governance Government Data 40

ProjectPro

OCTOBER 15, 2014

Does not have a dedicated metadata database. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Hadoop technology is the buzz word these days but most of the IT professionals still are not aware of the key components that comprise the Hadoop Ecosystem.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

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

Confluent

AUGUST 29, 2019

In an identity/access management application, it’s the relationships between roles and their privileges that matters most. If you’ve found yourself needing to write very large JOIN statements or dealing with long paths through your data, then you are probably facing a graph problem. Relationships act like verbs in your graph.

Kafka 55

Kafka Process Algorithm Cloud 55

Engineering at Meta

MARCH 18, 2024

Users can query using regular expressions on log lines, arbitrary metadata fields attached to logs, and across log files of hosts and services. Logarithm’s data model Logarithm represents logs as a named log stream of (host-local) time-ordered sequences of immutable unstructured text, corresponding to a single log file. in PyTorch).

Engineering 89

Engineering Metadata Architecture Designing 89

Snowflake

NOVEMBER 2, 2023

To give customers flexibility for how they fit Snowflake into their architecture, Iceberg Tables can be configured to use either Snowflake or an external service like AWS Glue as the tables’s catalog to track metadata, with an easy one-line SQL command to convert to Snowflake in a metadata-only operation.

Data Lake 92

Data Lake Data Warehouse Cloud Unstructured Data 92

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

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

Rockset

DECEMBER 22, 2020

We will also need to store this data in Elasticsearch. Whether you have each of these types of data in one index or separate doesn’t matter as we will be accessing them separately and joining them within our application.

SQL 40

SQL Data MongoDB Aggregated Data 40

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

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 57

Management Metadata Software Engineer Software Engineering 57

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

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 86

Systems Hadoop Metadata Telecommunication 86

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 71

Bytes Google Cloud Cloud Storage Utilities 71

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

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

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 85

Engineering Raw Data Data Science Scala 85

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

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

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 87

Data Warehouse Cloud Government Metadata 87

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 94

Media Database Metadata Data Schemas 94