Snowflake

APRIL 2, 2025

Traditional databases excelled at structured data and transactional workloads but struggled with performance at scale as data volumes grew. The data warehouse solved for performance and scale but, much like the databases that preceded it, relied on proprietary formats to build vertically integrated systems.

Data Lake 96

Data Lake Cloud Storage Metadata Data Warehouse 96

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

Cloudera

MAY 23, 2024

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes. This makes gathering information for decision making a challenge.

Systems 80

Systems Building Management Data Lake 80

U-Next

FEBRUARY 16, 2023

As my thoughts started wandering around our Banking systems and Cosmos Bank Cyber-attack 2018. There is a rapid increase in banking frauds like identity theft, phishing, vishing, smishing, access to debit/credit card details, and UPI/QR code scams. The system should time and again monitor and report audit authorities.

Banking 74

Banking Systems Education Government 74

Data Engineering Weekly

MARCH 5, 2025

Data Silos: Breaking down barriers between data sources. Hadoop achieved this through distributed processing and storage, using a framework called MapReduce and the Hadoop Distributed File System (HDFS). Start the Data Governance Process: Don't wait until the last minute to build the data governance framework.

Hadoop 57

Hadoop Metadata Data Ingestion Data Governance 57

Data Engineering Weekly

FEBRUARY 9, 2025

I found the product blog from QuantumBlack gives a view of data quality in unstructured data. link] Pinterest: Advancements in Embedding-Based Retrieval at Pinterest Homefeed Pinterest writes about its embedding-based retrieval system enhancements for Homefeed personalization and engagement.

Data Engineering 57

Data Engineering Data Engineer Engineering Unstructured Data 57

AltexSoft

JULY 27, 2021

You’ll learn about the types of recommender systems, their differences, strengths, weaknesses, and real-life examples. Personalization and recommender systems in a nutshell. Primarily developed to help users deal with a large range of choices they encounter, recommender systems come into play. Amazon, Booking.com) and.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

Snowflake

MARCH 14, 2024

Along with SNP Glue, the Snowflake Native App gives customers a simple, flexible and cost-effective solution to get data out of SAP and into Snowflake quickly and accurately. What’s the challenge with unlocking SAP data? Getting direct access to SAP data is critical because it holds such a breadth of ERP information.

IT 119

IT Data Ingestion Data AWS 119

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 113

Coding Building Management Government 113

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 105

Engineering Raw Data Data Science Machine Learning 105

Striim

SEPTEMBER 11, 2024

Understanding the essential components of data pipelines is crucial for designing efficient and effective data architectures. Here are six key components that are fundamental to building and maintaining an effective data pipeline. It offers scalable and high-performance tools that enable efficient data access and utilization.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

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 114

Data Lake Data Warehouse Cloud Unstructured Data 114

Snowflake

JUNE 4, 2024

Meanwhile, machine learning (ML) remains valuable in established areas of predictive AI, like recommendation systems, demand forecasting and fraud prevention. Users with access to the custom models will be able to use them just as easily as any other Cortex supported LLMs using the COMPLETE function in Cortex AI.

Data Security 120

Data Security Machine Learning Unstructured Data SQL 120

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Architecture 124

Architecture Metadata Kafka Government 124

Edureka

APRIL 14, 2025

The Real-World Example: Retail Giant’s Data Journey will be examined next. Real-World Example: Retail Giant’s Data Journey Take ShopSphere, a multinational retailer managing data from stores, online sales, feedback systems, and logistics. Conversely, the reporting tool shines in front-end customization.

BI 40

BI Business Intelligence Raw Data Retail 40

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

Lyft Engineering

MAY 5, 2025

This article explores real-time spatial temporal forecasting models and system designs used for predicting market conditions, focusing on how their complexity and rapid nature affect model performance, selection, and forecasting systemdesign. These are saved into a model artifacts database for online models to access.

Machine Learning 41

Machine Learning Architecture Kafka Systems 41

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 112

IT Unstructured Data Data Architecture Government 112

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

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

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 98

Data Governance Government Generalist Data Engineering 98

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

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 98

Programming Python Data Schemas Java 98

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 Algorithm Manufacturing 114

Cloudera

APRIL 1, 2024

We’re excited to share that Gartner has recognized Cloudera as a Visionary among all vendors evaluated in the 2023 Gartner® Magic Quadrant for Cloud Database Management Systems. Download the complimentary 2023 Gartner Magic Quadrant for Cloud Database Management Systems report.

Cloud 105

Cloud Unstructured Data Metadata Government 105

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 119

Generalist Telecommunication Healthcare Data Science 119

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

MARCH 12, 2025

For example, when theres an issue, only the ML, BE, or engineers have access to the AI stack, system, and logs to understand the issue, and only the data scientists have the expertise to actually solve it. With that expansion comes new challenges and new learning opportunities when it comes to GenAI development.

AWS 52

AWS Google Cloud Unstructured Data Coding 52

Monte Carlo

MARCH 12, 2025

For example, when theres an issue, only the ML, BE, or engineers have access to the AI stack, system, and logs to understand the issue, and only the data scientists have the expertise to actually solve it. With that expansion comes new challenges and new learning opportunities when it comes to GenAI development.

AWS 52

AWS Google Cloud Unstructured Data Coding 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 97

Coding SQL Database Data Cleanse 97

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 Machine Learning Business Intelligence 97

Edureka

FEBRUARY 12, 2025

Flexibility and Modularity : The modular design of LangChain lets coders change how parts work, connect them to other systems, and try out different setups. External API Calls LLMs can talk to APIs to get data in real time, do calculations, or connect to outside systems like databases and search engines. How does LangChain work?

IT 52

IT Database Google Cloud Coding 52

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 83

Medical Government Hospitality Electronics 83

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 Python Data Pipeline 102