Netflix Tech

SEPTEMBER 18, 2024

Second, developers had to constantly re-learn new data modeling practices and common yet critical data access patterns. To overcome these challenges, we developed a holistic approach that builds upon our Data Gateway Platform. Each namespace may use different backends: Cassandra, EVCache, or combinations of multiple.

Bytes 104

Bytes Metadata Database Data 104

Edureka

MARCH 20, 2025

These scams often target passwords, banking details, or sensitive organizational data by posing as a boss or coworker requesting confidential information. These apps may silently harvest personal data or metadata and, in some cases, install malware onto the device.

Banking 52

Banking Entertainment Media Transportation 52

Rockset

APRIL 18, 2023

Vector search has seen an explosion in popularity due to improvements in accuracy and broadened accessibility to the models used to generate embeddings. Rockset offers a number of benefits along with vector search support to create relevant experiences: Real-Time Data: Ingest and index incoming data in real-time with support for updates.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

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. High latency of data access. scalability.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Cloudera

SEPTEMBER 15, 2022

Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. There are also newer AI/ML applications that need data storage, optimized for unstructured data using developer friendly paradigms like Python Boto API. Diversity of workloads. LEGACY Bucket.

Systems 87

Systems Hadoop Metadata Telecommunication 87

ProjectPro

FEBRUARY 8, 2023

When Glue receives a trigger, it collects the data, transforms it using code that Glue generates automatically, and then loads it into Amazon S3 or Amazon Redshift. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog. being data exactly matches the classifier, and 0.0 Why Use AWS Glue?

AWS 98

AWS Scala Metadata Data Lake 98

Cloudera

NOVEMBER 23, 2021

Apache Knox Gateway provides perimeter security so that the enterprise can confidently extend access to new users. Security and governance policies are set once and applied across all data and workloads. The SDX layer of CDP leverages the full spectrum of Atlas to automatically track and control all data assets. Apache HBase.

Database 91

Database Non-relational Database NoSQL Government 91

Towards Data Science

DECEMBER 1, 2023

Storage —  Snowflake Snowflake, a cloud-based data warehouse tailored for analytical needs, will serve as our data storage solution. The data volume we will deal with is small, so we will not try to overkill with data partitioning, time travel, Snowpark, and other Snowflake advanced capabilities.

Data Engineering 97

Data Engineering Data Engineer Project Engineering 97

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. One IT-step away from a life outside the shadows.

IT 94

IT Data Lake Data Warehouse Cloud Storage 94

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 97

Media Database Metadata Data Schemas 97

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

Data Engineering Weekly

DECEMBER 16, 2024

Organizations across industries moved beyond experimental phases to implement production-ready GenAI solutions within their data infrastructure. Natural Language Interfaces Companies like Uber, Pinterest, and Intuit adopted sophisticated text-to-SQL interfaces, democratizing data access across their organizations.

Data Engineering 63

Data Engineering Data Engineer Engineering Unstructured Data 63

RandomTrees

SEPTEMBER 17, 2024

Understanding the Object Hierarchy in Metastore Identifying the Admin Roles in Unity Catalog Unveiling Data Lineage in Unity Catalog: Capture and Visualize Simplifying Data Access using Delta Sharing 1. Improved Data Discovery The tagging and documentation features in Unity Catalog facilitate better data discovery.

Data Governance 52

Data Governance Government Metadata Machine Learning 52

Towards Data Science

JANUARY 17, 2024

Parquet vs ORC vs Avro vs Delta Lake Photo by Viktor Talashuk on Unsplash The big data world is full of various storage systems, heavily influenced by different file formats. These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction.

Big Data 97

Big Data Data Data Storage SQL 97

Precisely

JANUARY 25, 2024

Today’s cloud systems excel at high-volume data storage, powerful analytics, AI, and software & systems development. You must carefully consider various mainframe functions, including security, system logs, metadata, and COBOL copybooks when moving to the new cloud platform. Best Practice 2. Best Practice 3.

Metadata 69

Metadata Relational Database Data Governance Government 69

Cloudera

OCTOBER 15, 2021

With FSO, Apache Ozone guarantees atomic directory operations, and renaming or deleting a directory is a simple metadata operation even if the directory has a large set of sub-paths (directories/files) within it. In fact, this gives Apache Ozone a significant performance advantage over other object stores in the data analytics ecosystem.

Cloud 87

Cloud Hadoop Data Analytics Metadata 87

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

phData: Data Engineering

SEPTEMBER 19, 2023

This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake? What are Data Modeling Methodologies, and Why Are They Important for a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Data Engineering Weekly

MARCH 24, 2024

The APIs support emitting unstructured log lines and typed metadata key-value pairs (per line). The extracted key-value pairs are written to the line’s metadata. Query clusters support interactive and bulk queries on one or more log streams with predicate filters on log text and metadata.

Data Engineering 63

Data Engineering Data Engineer Engineering Metadata 63

Towards Data Science

AUGUST 8, 2023

Where we started In the mid-2010s, data teams began migrating to the cloud and adopting data storage and compute technologies — Redshift, Snowflake, Databricks, GCP, oh my! — to The cloud made data faster to process, easier to transform and far more accessible. to meet the growing demand for analytics.

Coding 98

Coding Data Software Engineering Software Engineer 98

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Table of Contents What is data lakehouse architecture? The 5 key layers of data lakehouse architecture 1. Storage layer 3. Metadata layer 4. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Table of Contents What is data lakehouse architecture? The 5 key layers of data lakehouse architecture 1. Storage layer 3. Metadata layer 4. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Precisely

FEBRUARY 9, 2024

But few organizations have the data integrity required to power meaningful outcomes. Organizations must focus on breaking down silos and integrating all relevant, critical data into on-premises or cloud storage for AI model training and inference.

Data Integration 69

Data Integration Government Data Metadata 69

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

LinkedIn Engineering

JULY 27, 2023

It’s now much easier to manage large infra requirements that have traditionally demanded an amalgamation of teams like DBA, Infra-SRE, Onprem-SMEs, network managers, and access control managers working together. Data connections are secured through Azure Key Vaults and network connectivity is protected by LinkedIn's NACL control.

Metadata 75

Metadata Utilities Cloud Database 75

Snowflake

MARCH 30, 2023

Snowflake can also ingest external tables from on-premise s data sources via S3-compliant data storage APIs. Batch/file-based data is modeled into the raw vault table structures as the hub, link, and satellite tables illustrated at the beginning of this post.

Engineering 105

Engineering Raw Data Data Science Machine Learning 105

Knowledge Hut

JULY 24, 2023

In this article, we will explore the concept of data independence in relational databases and how it can benefit your organization by allowing you to work more effectively with your data while ensuring it always remains accessible and secure. What is Data Independence of DBMS? Physical Data Independence in DBMS 1.

Database Design 52

Database Design Relational Database Database Metadata 52

Monte Carlo

MAY 30, 2023

It’s designed to improve upon the performance and usability challenges of older data storage formats such as Apache Hive and Apache Parquet. Choose the right partitioning strategy Partitioning can significantly improve query performance by reducing the amount of data scanned.

Metadata 52

Metadata Raw Data Data Lake Data 52

Monte Carlo

AUGUST 25, 2023

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. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Databand.ai

JUNE 28, 2023

Having a bigger and more specialized data team can help, but it can hurt if those team members don’t coordinate. More people accessing the data and running their own pipelines and their own transformations causes errors and impacts data stability. is a unified data observability platform built for data engineers.

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. 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.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 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. Another type of data storage — a data lake — tried to address these and other issues. Data lake. DataFrame API support.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

SEPTEMBER 16, 2021

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies. Hence, writes in Hbase are operation intensive.

NoSQL 52

NoSQL Database Hadoop Big Data 52

AltexSoft

OCTOBER 30, 2021

Here, data scientists are supported by data engineers. Data engineering itself is a process of creating mechanisms for accessing data. Data engineer’s integral task is building and maintaining data infrastructure — the system managing the flow of data from its source to destination.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

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

Monte Carlo

JUNE 28, 2022

Traditionally, data lakes held raw data in its native format and were known for their flexibility, speed, and open source ecosystem. By design, data was less structured with limited metadata and no ACID properties. Unity Catalog The Unity Catalog unifies metastores, catalogs, and metadata within Databricks.

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52