Snowflake

NOVEMBER 11, 2024

Deliver multimodal analytics with familiar SQL syntax Database queries are the underlying force that runs the insights across organizations and powers data-driven experiences for users. Traditionally, SQL has been limited to structured data neatly organized in tables.

Unstructured Data 95

Unstructured Data SQL AWS Healthcare 95

Data Engineering Weekly

OCTOBER 27, 2024

Astasia Myers: The three components of the unstructured data stack LLMs and vector databases significantly improved the ability to process and understand unstructured data. I never thought of PDF as a self-contained document database, but that seems a reality that we can’t deny.

Data Engineering 59

Data Engineering Data Engineer Engineering Unstructured Data 59

ProjectPro

JUNE 6, 2025

Explore how to implement Graph RAG using Knowledge Graphs and Vector Databases with practical insights, hands-on resources, and advanced techniques for enhanced information retrieval. Knowledge Graph vs Vector Database for RAG How to implement Graph RAG using Knowledge Graphs and Vector Databases?

Building 52

Building Unstructured Data Database Datasets 52

ProjectPro

JUNE 6, 2025

” This blog will align with that vision by exploring what Pinecone Vector Database is, how to use Pinecone Vector Database, and explore a comprehensive Pinecone Vector Database tutorial with a simple example. Table of Contents What is a Pinecone Vector Database?

Database 40

Database Project Metadata Unstructured Data 40

RandomTrees

NOVEMBER 25, 2024

One of the primary issues is data privacy. Telecom operators have a lot of sensitive information relating to customers on their databases, and employing AI in evaluating this data raises the question of how it is safeguarded. Overcoming Implementation Challenges The project faced some difficulties along the way.

Telecommunication 52

Telecommunication IT Unstructured Data Data Mining 52

ProjectPro

JUNE 6, 2025

Learn to Interact with the DBMS Systems Many companies keep their data warehouses far from the stations where data can be accessed. The role of a data engineer is to use tools for interacting with the database management systems. for working on cloud data warehouses.

Data Engineering 58

Data Engineering Data Engineer Engineering Amazon Web Services 58

databricks

JUNE 18, 2025

Imagine you’re building a customer support agent that helps support representatives at your telcom company. 160 Spear Street, 15th Floor San Francisco, CA 94105 1-866-330-0121 See Careers at Databricks © Databricks 2025. 160 Spear Street, 15th Floor San Francisco, CA 94105 1-866-330-0121 See Careers at Databricks © Databricks 2025.

Management 75

Management Entertainment Manufacturing Retail 75

Snowflake

JULY 15, 2025

In 2024, Anthropic open sourced the Model Context Protocol (MCP), a standard that enables AI agents to securely interact with enterprise systems where data resides, such as content repositories, business applications, development environments and databases.

Unstructured Data 104

Unstructured Data Government Data Accessible 104

ProjectPro

JUNE 6, 2025

Explore the world of data analytics with the top AWS databases! Check out this blog to discover your ideal database and uncover the power of scalable and efficient solutions for all your data analytical requirements. Let’s understand more about AWS Databases in the following section.

AWS 40

AWS Database Amazon Web Services MySQL 40

ProjectPro

JUNE 6, 2025

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.

NoSQL 40

NoSQL Database Hadoop Big Data 40

ProjectPro

JUNE 6, 2025

Physical data model- The physical data model includes all necessary tables, columns, relationship constraints, and database attributes for physical database implementation. A physical model's key parameters include database performance, indexing approach, and physical storage. It makes data more accessible.

Data Warehouse 53

Data Warehouse NoSQL PostgreSQL Relational Database 53

RudderStack

JUNE 24, 2025

Manager, Technical Marketing Content Get the newsletter Subscribe to get our latest insights and product updates delivered to your inbox once a month As organizations adopt more tools and platforms, their data becomes increasingly fragmented across systems. What is data federation?

IT 59

IT Data Consolidation Metadata Government 59

ProjectPro

JUNE 6, 2025

The volume and the variety of data captured have also rapidly increased, with critical system sources such as smartphones, power grids, stock exchanges, and healthcare adding more data sources as the storage capacity increases. Data Ingestion is usually the first step in the data engineering project lifecycle.

Data Ingestion 45

Data Ingestion Data Engineering Data Engineer Project 45

ProjectPro

JUNE 6, 2025

Data engineering tools are specialized applications that make building data pipelines and designing algorithms easier and more efficient. These tools are responsible for making the day-to-day tasks of a data engineer easier in various ways. This is important since big data can be structured or unstructured or any other format.

Data Engineering 45

Data Engineering Data Engineer Engineering Kafka 45

databricks

JULY 18, 2025

As one of the largest nonprofit health systems in the United States—with 51 hospitals, over 1,000 outpatient clinics, and more than 130,000 caregivers across seven states—our ability to deliver timely, coordinated care depends on transforming not only clinical outcomes but also the workflows that support them.

Entertainment 86

Entertainment Healthcare Manufacturing Retail 86

ProjectPro

JUNE 6, 2025

Data is often referred to as the new oil, and just like oil requires refining to become useful fuel, data also needs a similar transformation to unlock its true value. This transformation is where data warehousing tools come into play, acting as the refining process for your data. Automatic data backups and replication.

Data Storage 58

Data Storage PostgreSQL Data Warehouse AWS 58

ProjectPro

JUNE 6, 2025

Graduating from ETL Developer to Data Engineer Career transitions come with challenges. Suppose you are already working in the data industry as an ETL developer. You can easily transition to other data-driven jobs such as data engineer , analyst, database developer, and scientist.

Data Engineering 59

Data Engineering Data Engineer Engineering ETL Tools 59

ProjectPro

JUNE 6, 2025

Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., and Flume in Hadoop is used to sources data which is stored in various sources like and deals mostly with unstructured data. The complexity of the big data system increases with each data source.

ETL Tools 40

ETL Tools Hadoop Relational Database Unstructured Data 40

Cloudera

NOVEMBER 15, 2024

Enterprise organizations collect massive volumes of unstructured data, such as images, handwritten text, documents, and more. They also still capture much of this data through manual processes. The way to leverage this for business insight is to digitize that data.

Machine Learning 85

Machine Learning Unstructured Data Project Database 85

ProjectPro

JUNE 6, 2025

Programming Language.NET and Python Python and Scala AWS Glue vs. Azure Data Factory Pricing Glue prices are primarily based on data processing unit (DPU) hours. Azure Data Factory SSIS Support ADF provides native support for SSIS packages so its easier to migrate SSIS packages unlike AWS Glue that does not provide native support.

AWS 40

AWS Cloud Amazon Web Services ETL Tools 40

ProjectPro

JUNE 6, 2025

This serverless data integration service can automatically and quickly discover structured or unstructured enterprise data when stored in data lakes in Amazon S3, data warehouses in Amazon Redshift, and other databases that are a component of the Amazon Relational Database Service.

AWS 66

AWS Scala Metadata Data Lake 66

ProjectPro

JUNE 6, 2025

A data architect, in turn, understands the business requirements, examines the current data structures, and develops a design for building an integrated framework of easily accessible, safe data aligned with business strategy. Table of Contents What is a Data Architect Role?

Data Architect 40

Data Architect Data Mining Programming Language Java 40

databricks

JULY 21, 2025

Apply recursive CTEs to tasks like dependency resolution, graph traversal, and nested data processing. See examples below of each including RCTEs leveraging the Variant data type for JSON hierarchies. Plus, support for recursive CTEs simplifies migrations from legacy database systems.

Entertainment 57

Entertainment Manufacturing SQL Retail 57

Snowflake

JUNE 10, 2025

For years, Snowflake has been laser-focused on reducing these complexities, designing a platform that streamlines organizational workflows and empowers data teams to concentrate on what truly matters: driving innovation. This native integration streamlines development and accelerates the delivery of transformed data.

Data Pipeline 81

Data Pipeline SQL Python Building 81

ProjectPro

JUNE 6, 2025

So, have you been wondering what happens to all the data collected from different sources, logs on your machine, data generated from your mobile, data in databases, customer data, and so on? We can do a lot of data analysis and produce visualizations to deliver value from these data sources.

Data Science 40

Data Science Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

If you're wondering how the ETL process can drive your company to a new era of success, this blog will help you discover what use cases of ETL make it a critical component in many data management and analytic systems. Business Intelligence - ETL is a key component of BI systems for extracting and preparing data for analytics.

BI 45

BI ETL Tools Retail Healthcare 45

Jesse Anderson

MAY 5, 2025

Finally, Shane outlines how observability is crucial for emerging AI/ML workflows like RAG pipelines, discussing the monitoring of vector databases (like Pinecone), unstructured data, and the entire AI system lifecycle, concluding with a look at Monte Carlo’s exciting roadmap, including AI-powered troubleshooting agents.

Unstructured Data 130

Unstructured Data Finance Metadata Architecture 130

ProjectPro

JUNE 6, 2025

The auto-replication of BigQuery across international data centers is one of its key benefits, significantly reducing the possibility of service outages and downtime. Key Tools Snowflake offers a comprehensive collection of tools to manage every aspect of data input, transformation, and analytics, including unstructured data.

Data Warehouse 40

Data Warehouse Cloud Google Cloud Big Data 40

ProjectPro

JUNE 6, 2025

Say goodbye to database downtime, and hello to Amazon Aurora! Explore the advanced features of this powerful cloud-based solution and take your data management to the next level with this comprehensive guide. A detailed study report by Market Research Future (MRFR) projects that the cloud database market value will likely reach USD 38.6

Database 40

Database Technology Cloud PostgreSQL 40

ProjectPro

JUNE 6, 2025

." - Matt Glickman, VP of Product Management at Databricks Data Warehouse and its Limitations Before the introduction of Big Data, organizations primarily used data warehouses to build their business reports. Lack of unstructured data, less data volume, and lower data flow velocity made data warehouses considerably successful.

Data Lake 63

Data Lake Data Warehouse Metadata Unstructured Data 63

Snowflake

MARCH 6, 2025

Large language models (LLMs) are transforming how we extract value from this data by running tasks from categorization to summarization and more. While AI has proved that real-time conversations in natural language are possible with LLMs, extracting insights from millions of unstructured data records using these LLMs can be a game changer.

Unstructured Data 90

Unstructured Data Medical Media Data Workflow 90

ProjectPro

JUNE 6, 2025

Many leading brands like the Walt Disney Company, Koch Industries Inc, LTK, Amgen, and more use Amazon Redshift for optimizing their data science workflows. Table of Contents AWS Redshift Data Warehouse Architecture 1. Databases Top10 AWS Redshift Project Ideas and Examples for Practice AWS Redshift Projects for Beginners 1.

AWS 64

AWS Data Pipeline Project Building 64

ProjectPro

JUNE 6, 2025

During peak hours, the pipeline handles around ~8 million events per second, with a data throughput reaching ~24 gigabytes per second. This data infrastructure forms the backbone for analytics, machine learning algorithms , and other critical systems that drive content recommendations, user personalization, and operational efficiency.

Data Engineering 40

Data Engineering Data Engineer Engineering NoSQL 40

ProjectPro

JUNE 6, 2025

Building on the growing relevance of RAG pipelines, this blog offers a hands-on guide to effectively understanding and implementing a retrieval-augmented generation system. It discusses the RAG architecture, outlining key stages like data ingestion , data retrieval, chunking , embedding generation , and querying.

Building 40

Building Project Metadata Data Ingestion 40

ProjectPro

JUNE 6, 2025

Ever wished for a database that's as easy to use as your favorite app? Say hello to AWS DocumentDB - your passport to unlocking the simplicity of data management. It's like a magic tool that makes handling data super simple. ” AWS DocumentDB is a fully managed, NoSQL database service provided by Amazon Web Services (AWS).

AWS 40

AWS Database MongoDB Management 40

ProjectPro

JUNE 6, 2025

With global data creation expected to soar past 180 zettabytes by 2025, businesses face an immense challenge: managing, storing, and extracting value from this explosion of information. Traditional data storage systems like data warehouses were designed to handle structured and preprocessed data.

Data Lake 40

Data Lake Building Hadoop Raw Data 40

ProjectPro

JUNE 6, 2025

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). Data is regularly updated.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40