Snowflake

JULY 10, 2023

Processing files in a Python UDF and Stored Procedure has piqued the interest of our data scientists and paves the way for automation of new, complex data pipelines.” Mike Tuck, Air Pollution Specialist Why unstructured data?

Unstructured Data 40

Unstructured Data Python Process Scala 40

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

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. Understanding the data sets to be replicated from the CDH Cluster.

Cloud 71

Cloud Data Lake Cloud Storage Metadata 71

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

Monte Carlo

JULY 13, 2023

Utilizing a data permissions scanner and posture manager ensures that data engineers are informed about who has the potential to access data, which helps mitigate this risk. Automated processes scan all data stores and discover data, including semi-structured data such as JSON on a continual basis.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Data Engineering Podcast

FEBRUARY 3, 2019

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. What are your protocols for determining which data sets you will work with?

Digital Media 100

Digital Media Media PostgreSQL Datasets 100

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

Hepta Analytics

FEBRUARY 14, 2022

Disadvantages of a data lake are: Can easily become a data swamp data has no versioning Same data with incompatible schemas is a problem without versioning Has no metadata associated It is difficult to join the data Data warehouse stores processed data, mostly structured data.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Rockset

APRIL 26, 2023

These vector search queries are written to find similarities between products, while filtering both real-time metadata, like product availability, and historical metadata, like a user’s previous purchases. This will simplify your architecture considerably, deliver low-latency recommendation results, and enable metadata filtering.

Architecture 52

Architecture Transportation Data Lake Insurance 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

Cloudera

SEPTEMBER 17, 2020

They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. Events or time-series data served by our real-time events or time-series data store solutions.

Unstructured Data 81

Unstructured Data Data Warehouse Pharmaceutical MySQL 81

Rockset

DECEMBER 17, 2021

For those unfamiliar, DynamoDB makes database scalability a breeze, but with some major caveats.

SQL 52

SQL NoSQL Database Design Metadata 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

Striim

JANUARY 4, 2023

This means that your contract should include metadata about your schema, which you can use to describe your data and add value constraints for certain fields (e.g., Ensure data contracts don’t affect iteration speed for software developers. Apache Avro) to serialize and deserialize structured data. temperature).

PostgreSQL 52

PostgreSQL Data Warehouse Data Lake Data 52

Rockset

AUGUST 2, 2023

The steps Windward takes to create proprietary data and AI insights As Windward operated in a batch-based data stack, they stored raw data in S3. They used MongoDB as their metadata store to capture vessel and company data.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

Rockset

FEBRUARY 21, 2019

Which is a great reason for Rockset to support SQL queries on PDF files, in our mission to make data more usable to everyone. Now add PDFs to the mix, and users can combine PDF data with data of other formats, from various sources, into their SQL analyses. . from the document along with the text.

SQL 52

SQL Metadata Structured Data IT 52

Ascend.io

AUGUST 31, 2023

Stepwise Transformation: Structuring data transformation in sequential steps provides clarity and control over sophisticated data operations such as business validation, data normalization, and analytics functions.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Databand.ai

NOVEMBER 4, 2022

How Databand can help Databand empowers data platform teams to deliver reliable and trustworthy data. In other words, it allows you to catch bad data before it impacts your business.

Data 52

Data Data Pipeline Retail Metadata 52

Grouparoo

JANUARY 11, 2022

A data warehouse is a unified repository where data from diverse sources undergo aggregation and integration into a usable source of information. To achieve this, a data warehouse will require processes to gather and integrate data, manage data quality, create metadata, and support any regulatory compliance and governance procedures.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 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 73

Big Data Data Data Storage SQL 73

Knowledge Hut

DECEMBER 21, 2023

Avro creates binary data which can be both compressed as well as split. Avro creates a file that stores all the data and saves the schema in the metadata section. Pros: Avro stores data in a compact and efficient manner. It can easily convert unstructured data to structured data.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Monte Carlo

JANUARY 25, 2023

The contracts themselves should be created using well-established protocols for serializing and deserializing structured data such as Google’s Protocol Buffers (protobuf), Apache Avro, or even JSON. We can specify the fields of the contract in addition to metadata like ownership, SLA, and where the table is located.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

Monte Carlo

JULY 10, 2023

Data sampling If you’re working with large data sets where it’s impractical to evaluate every attribute or record, you can systematically sample your data set to estimate completeness. Be sure to use random sampling to select representative subsets of your data.

Data Collection 40

Data Collection Data Governance Government Data 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

ProjectPro

OCTOBER 15, 2014

Hive- Performance Benchmarking Hive vs Pig Pig vs Hive - Differences Pig Hive Procedural Data Flow Language Declarative SQLish Language For Programming For creating reports Mainly used by Researchers and Programmers Mainly used by Data Analysts Operates on the client side of a cluster. Does not have a dedicated metadata database.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

Monte Carlo

MARCH 14, 2023

In an effective data mesh, data governance tools need to be standardized,” said Kineret. And part of that is data observability and data quality. Anything around metadata, performance, and quality should be standardized.

Transportation 40

Transportation Government Google Cloud Architecture 40

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 91

Engineering Metadata Architecture Designing 91

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

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

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 91

Data Lake Data Warehouse Cloud Unstructured Data 91

Data Engineering Podcast

JUNE 17, 2021

Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable. Can you describe what Unstruk Data is and the story behind it? How do you manage data enrichment/integration with structured data sources?

Unstructured Data 100

Unstructured Data Data Warehouse Metadata Media 100

Engineering at Meta

FEBRUARY 6, 2024

The script we use to generate DotSlash files injects metadata about the build job that makes it straightforward to trace the provenance of the underlying artifacts. The following is a hypothetical example of a generated DotSlash file for the CodeCompose LSP built from source at a specific commit in clang-opt mode.

Metadata 117

Metadata Coding Building Project 117

Confluent

AUGUST 29, 2019

Instead of storing tables and columns, Neo4j represents all data as a graph, meaning that the data is a set of nodes with labels and relationships. Nodes are like our data entities (in this example, we use Person ). This approach to structuring data is called the property graph model.

Kafka 55

Kafka Process Algorithm Cloud 55

Rockset

DECEMBER 22, 2020

We will also need to store this data in Elasticsearch. This becomes increasingly relevant when your queries may change frequently, when new features need to be implemented or when new data sources are introduced.

SQL 40

SQL Data MongoDB Aggregated Data 40

Zalando Engineering

JANUARY 30, 2023

Managing structured data in markdown is not ideal, despite the ability to use front matter for metadata. During the application review process it's indicated per application (from certain criticality tier onward) whether there are any playbooks defined for it and whether any of these are expired.

Management 57

Management Metadata Software Engineer Software Engineering 57

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