ThoughtSpot

MARCH 5, 2024

Create Snowflake dynamic tables In Snowflake, create dynamic tables by writing SQL queries that define how data should be transformed and materialized. Grant ThoughtSpot access In Snowflake, grant the ThoughtSpot service account USAGE privileges on the schemas containing the dynamic tables. Set refresh schedules as needed.

BI 111

BI Datasets SQL Raw Data 111

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

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. A file stored in the system ?an’t

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

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 114

IT Unstructured Data Data Architecture Government 114

Snowflake

MARCH 30, 2023

For this reason, a new data management for ML framework has emerged to help manage this complexity: the “feature store.” Feature store As described in Tecton’s blog , a feature store is a data management system for managing ML feature pipelines, including the management of feature engineering code and data.

Engineering 87

Engineering Raw Data Data Science Machine Learning 87

Snowflake

NOVEMBER 2, 2023

Rather than defining schema upfront, a user can decide which data and schema they need for their use case. Snowflake has long supported semi-structured data types and file formats like JSON, XML, Parquet, and more recently storage and processing of unstructured data such as PDF documents, images, videos, and audio files.

Data Lake 96

Data Lake Data Warehouse Cloud Unstructured Data 96

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. . This led them to fall behind.

Data Warehouse 83

Data Warehouse Unstructured Data Pharmaceutical MySQL 83

Knowledge Hut

FEBRUARY 29, 2024

A database is a structured data collection that is stored and accessed electronically. File systems can store small datasets, while computer clusters or cloud storage keeps larger datasets. According to a database model, the organization of data is known as database design.

Data Science 98

Data Science Datasets Machine Learning Database Design 98

Monte Carlo

JUNE 6, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Having the data engineering team lead the response to data quality is by far the most common pattern. It is deployed by about half of all organizations that use a modern data stack.

Data Governance 98

Data Governance Government Data Data Engineering 98

Snowflake

JUNE 5, 2024

It provides access to industry-leading large language models (LLMs), enabling users to easily build and deploy AI-powered applications. By using Cortex, enterprises can bring AI directly to the governed data to quickly extend access and governance policies to the models.

Coding 92

Coding Building Management Government 92

Cloudera

DECEMBER 11, 2020

As mentioned in my previous blog on the topic , the recent shift to remote working has seen an increase in conversations around how data is managed. Toolsets and strategies have had to shift to ensure controlled access to data. Driving innovation with secure and governed data .

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

Confluent

OCTOBER 3, 2019

We recently launched a new artificial intelligence (AI) data extraction API called Scrapinghub AutoExtract , which turns article and product pages into structured data. At Scrapinghub, we specialize in web data extraction , and our products empower everyone from programmers to CEOs to extract web data quickly and effectively.

Kafka 16

Kafka Cloud Amazon Web Services Google Cloud 16

U-Next

MARCH 1, 2023

They build scalable data processing pipelines and provide analytical insights to business users. A Data Engineer also designs, builds, integrates, and manages large-scale data processing systems. It’s not just the data itself that is important, but also how that data can be used to make better decisions.

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Edureka

JUNE 7, 2024

paintings, songs, code) Historical data relevant to the prediction task (e.g., Unlike traditional AI systems that operate on pre-existing data, generative AI models learn the underlying patterns and relationships within their training data and use that knowledge to create novel outputs that did not previously exist.

Deep Learning 114

Deep Learning Media Manufacturing Algorithm 114

Engineering at Meta

MARCH 18, 2024

Systems and application logs play a key role in operations, observability, and debugging workflows at Meta. We designed the system to support service-level guarantees on log freshness, completeness, durability, query latency, and query result completeness. PyTorch, data readers, checkpointing, framework code, and hardware).

Engineering 103

Engineering Metadata Architecture Designing 103

Cloudera

JULY 26, 2021

In fact, data product development introduces an additional requirement that wasn’t as relevant in the past as it is today: That of scalability in permissioning and authorization given the number and multitude of different roles of data constituents, both internal and external accessing a data product.

Generalist 120

Generalist Telecommunication Healthcare Data Science 120

Cloudera

SEPTEMBER 29, 2021

Among governments’ priorities are encouraging digital adoption, facilitating access and usage of relevant government services alongside enabling more digital transactions. Among the use cases for the government organizations that we are working on is one which leverages machine learning to detect fraud in payment systems nationwide.

Medical 85

Medical Government Hospitality Electronics 85

Snowflake

NOVEMBER 11, 2024

However, scaling LLM data processing to millions of records can pose data transfer and orchestration challenges, easily addressed by the user-friendly SQL functions in Snowflake Cortex. Traditionally, SQL has been limited to structured data neatly organized in tables.

Unstructured Data 81

Unstructured Data SQL AWS Healthcare 81

Knowledge Hut

DECEMBER 26, 2023

According to the Cybercrime Magazine, the global data storage is projected to be 200+ zettabytes (1 zettabyte = 10 12 gigabytes) by 2025, including the data stored on the cloud, personal devices, and public and private IT infrastructures. Data Analyst Scientist.

Data Science 97

Data Science BI Business Intelligence Machine Learning 97

Confluent

JUNE 13, 2019

This data pipeline is a great example of a use case for Apache Kafka ®. Observational astronomers study many different types of objects, from asteroids in our own solar system to galaxies that are billions of lightyears away. The technology underlying the ZTF system should be a prototype that reliably scales to LSST needs.

Kafka 102

Kafka Bytes Data Pipeline Python 102

Netflix Tech

DECEMBER 14, 2018

In the previous blog posts in this series, we introduced the N etflix M edia D ata B ase ( NMDB ) and its salient “Media Document” data model. In this post we will provide details of the NMDB system architecture beginning with the system requirements?—?these key value stores generally allow storing any data under a key).

Media 97

Media Database Metadata Data Schemas 97

Data Engineering Weekly

MAY 5, 2024

The motivation for Machine Unlearning is critical from the privacy perspective and for model correction, fixing outdated knowledge, and access revocation of the training dataset. link] LinkedIn: LakeChime - A Data Trigger Service for Modern Data Lakes LinkedIn points out two critical flaws in a partitioned approach to data management.

Data Engineering 67

Data Engineering Data Engineer Engineering Google Cloud 67

Towards Data Science

MAY 11, 2023

Sharvit deconstructs the elements of complexity that sometimes seems inevitable with OOP and summarizes the main principles of DOP that helps us make the system more manageable. As its name suggests, DOP puts data first and foremost. to control who can access/change data in Python. These principles are language-agnostic.

Programming 87

Programming Python Data Schemas Java 87

Netflix Tech

MARCH 5, 2019

This operational component places some cognitive load on our engineers, requiring them to develop deep understanding of telemetry and alerting systems, capacity provisioning process, security and reliability best practices, and a vast amount of informal knowledge about the cloud infrastructure.

Cloud 74

Cloud Building Amazon Web Services Metadata 74

Knowledge Hut

FEBRUARY 6, 2024

A Summary of day-to-day tasks carried out by a DevOps engineer - Design, build, test and deploy scalable, distributed systems from development through production Manage the code repository(such as Git, SVN, BitBucket, etc.) Who can become a DevOps Engineer? DevOps is a vast environment that fits almost all technologies and processes into it.

Engineering 98

Engineering Programming Language Amazon Web Services Google Cloud 98

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. What is Data Warehouse? . Built to make strategic use of data, a Data Warehouse is a combination of technologies and components. Data Warehouse in DBMS: .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Towards Data Science

JUNE 8, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Photo by Luke Chesser on Unsplash Having the data engineering team lead the response to data quality is by far the most common pattern. There are downsides to this approach however.

Data Governance 73

Data Governance Government Generalist Data Engineering 73

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). While functional, our current setup for managing tables is fragmented.

Big Data 78

Big Data Data Management Management Metadata 78

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

Data Management 52

Data Management Management Data Lake Data Governance 52

Snowflake

AUGUST 25, 2023

Our Code Llama fine-tuned (7b, 34b) for text-to-SQL outperforms base Code Llama (7b, 34b) by 16 and 9 percent-accuracy points respectively Evaluating performance of SQL-generation models Performance of our text-to-SQL models is reported against the “dev” subset of the Spider data set.

Coding 78

Coding SQL Data Cleanse Database 78

Netflix Tech

FEBRUARY 25, 2021

Since early 2020, Netflix has been iteratively developing systems to provide internal stakeholders and business leaders with up-to-date tools and dashboards with the latest information on the pandemic. Use PostgreSQL Composite Types when taking advantage of PostgreSQL Aggregate Functions.

PostgreSQL 82

PostgreSQL Database Entertainment SQL 82

Knowledge Hut

APRIL 23, 2024

Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data. Data warehousing offers several advantages. By structuring data in a predefined schema, data warehouses ensure data consistency and accuracy.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Data Engineering Weekly

APRIL 7, 2024

The emerging of composable data stack, and open data stack is certainly an interesting trend to watch. A key highlight for me, I spoke to multiple data people stuck in legacy systems and still inching their way to the cloud.

Data Engineering 70

Data Engineering Data Engineer Engineering Unstructured Data 70

Cloudera

NOVEMBER 15, 2024

Cyber defenders struggle with: Too much data: Cybersecurity tools generate an overwhelming volume of log data, including Domain Name Service (DNS) records, firewall logs, and more. All of this data is essential for investigations and threat hunting, but existing systems often struggle to manage it efficiently.

Metadata 59

Metadata Unstructured Data Data Lake Government 59

AltexSoft

AUGUST 4, 2021

Some sweets are presented on your display cases for quick access while the rest is kept in the storeroom. Now let’s think of sweets as the data required for your company’s daily operations. Initially, DWs dealt with structured data presented in tabular forms. Independent data marts. Data mart designing.

Data Lake 64

Data Lake Data Warehouse ETL Tools Database 64