Flipboard

JUNE 24, 2025

Musani emphasized the massive scale: “More than a million users doing 30,000 queries a day…that’s massive things happening on such rich data.” Unified data pipelines connect the supply chain to the store floor. As Musani explains: “We have built element in a way where it makes it agnostic to different llms as well, right? “We

AI 175

AI AI Data Scientist Data Pipeline 175

AWS Machine Learning Blog

FEBRUARY 21, 2025

The agent knowledge base stores Amazon Bedrock service documentation, while the cache knowledge base contains curated and verified question-answer pairs. For this example, you will ingest Amazon Bedrock documentation in the form of the User Guide PDF into the Amazon Bedrock knowledge base. This will be the primary dataset.

AWS 124

AWS Natural Language Processing Machine Learning Machine Learning 124

databricks

JUNE 12, 2025

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

SQL 221

SQL Data Engineering Data Engineering Data Engineer 221

Hacker News

JULY 1, 2025

Prior to that, I spent a couple years at First Orion - a smaller data company - helping found & build out a data engineering team as one of the first engineers. We were focused on building data pipelines and models to protect our users from malicious phonecalls. Oh, also, I'm great at writing documentation.

Python 69

Python AWS SQL ML 69

Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Learning these tools is crucial for building scalable data pipelines. offers Data Science courses covering these tools with a job guarantee for career growth. Below are 20 essential tools every data engineer should know.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Flipboard

JUNE 3, 2025

Amazon Elastic Kubernetes Service (Amazon EKS) retrieves data from Amazon DocumentDB , processes it, and invokes Amazon Bedrock Agents for reasoning and analysis. This structured data pipeline enables optimized pricing strategies and multilingual customer interactions.

AWS 140

AWS Apache Kafka Database AI 140

Women in Big Data

FEBRUARY 27, 2025

Big data pipelines are the backbone of modern data processing, enabling organizations to collect, process, and analyze vast amounts of data in real-time. Issues such as data inconsistencies, performance bottlenecks, and failures are inevitable.In Validate data format and schema compatibility.

Data Pipeline 59

Data Pipeline Big Data Big Data Data Quality 59

Smart Data Collective

SEPTEMBER 26, 2021

Working with massive structured and unstructured data sets can turn out to be complicated. It’s obvious that you’ll want to use big data, but it’s not so obvious how you’re going to work with it. So, let’s have a close look at some of the best strategies to work with large data sets. A document is susceptible to change.

Database 130

Database Data Visualization Big Data Big Data 130

AWS Machine Learning Blog

FEBRUARY 1, 2024

Data pipelines In cases where you need to provide contextual data to the foundation model using the RAG pattern, you need a data pipeline that can ingest the source data, convert it to embedding vectors, and store the embedding vectors in a vector database.

AWS 137

AWS AI AI Database 137

The MLOps Blog

JUNE 27, 2023

User support arrangements Consider the availability and quality of support from the provider or vendor, including documentation, tutorials, forums, customer service, etc. Databricks Databricks is a cloud-native platform for big data processing, machine learning, and analytics built using the Data Lakehouse architecture.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Smart Data Collective

JULY 15, 2021

Once your information is organized, a data observability tool can take your data quality efforts to the next level by managing data drift or schema drift before they break your data pipelines or affect any downstream analytics applications. What Does a Data Catalog Do?

Data Quality 133

Data Quality Database Data Pipeline Data Observability 133

DagsHub

DECEMBER 11, 2023

It does not support the ‘dvc repro’ command to reproduce its data pipeline. DVC Released in 2017, Data Version Control ( DVC for short) is an open-source tool created by iterative. However, these tools have functional gaps for more advanced data workflows. Git LFS requires a LFS server to work.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Data Science 98

AWS Machine Learning Blog

SEPTEMBER 18, 2024

It simplifies feature access for model training and inference, significantly reducing the time and complexity involved in managing data pipelines. Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly. Saurabh Gupta is a Principal Engineer at Zeta Global.

AWS 121

AWS Machine Learning Machine Learning ML 121

ODSC - Open Data Science

OCTOBER 18, 2024

The advent of big data, affordable computing power, and advanced machine learning algorithms has fueled explosive growth in data science across industries. However, research shows that up to 85% of data science projects fail to move beyond proofs of concept to full-scale deployment.

Data Science 52

Data Science Data Scientist Analytics Data Quality 52

DagsHub

OCTOBER 23, 2024

With proper unstructured data management, you can write validation checks to detect multiple entries of the same data. Continuous learning: In a properly managed unstructured data pipeline, you can use new entries to train a production ML model, keeping the model up-to-date.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

IBM Journey to AI blog

OCTOBER 12, 2023

Securing AI models and their access to data While AI models need flexibility to access data across a hybrid infrastructure, they also need safeguarding from tampering (unintentional or otherwise) and, especially, protected access to data. Bias can also find its way into a model’s outputs long after deployment.

AI 93

AI AI Data Scientist Data Governance 93

ODSC - Open Data Science

SEPTEMBER 29, 2023

But, the amount of data companies must manage is growing at a staggering rate. Research analyst firm Statista forecasts global data creation will hit 180 zettabytes by 2025. In our discussion, we cover the genesis of the HPCC Systems data lake platform and what makes it different from other big data solutions currently available.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

Flipboard

NOVEMBER 24, 2023

The SnapLogic Intelligent Integration Platform (IIP) enables organizations to realize enterprise-wide automation by connecting their entire ecosystem of applications, databases, big data, machines and devices, APIs, and more with pre-built, intelligent connectors called Snaps.

Database 158

Database AWS ETL SQL 158

Pickl AI

OCTOBER 10, 2024

Enhanced Data Quality : These tools ensure data consistency and accuracy, eliminating errors often occurring during manual transformation. Scalability : Whether handling small datasets or processing big data, transformation tools can easily scale to accommodate growing data volumes.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

Pickl AI

JUNE 7, 2024

Open-Source Community: Airflow benefits from an active open-source community and extensive documentation. IBM Infosphere DataStage IBM Infosphere DataStage is an enterprise-level ETL tool that enables users to design, develop, and run data pipelines. Read More: Advanced SQL Tips and Tricks for Data Analysts.

ETL 40

ETL Data Quality Data Warehouse Data Pipeline 40

Pickl AI

OCTOBER 10, 2023

In today’s fast-paced business environment, the significance of Data Observability cannot be overstated. Data Observability enables organizations to detect anomalies, troubleshoot issues, and maintain data pipelines effectively. This involves creating data dictionaries, documentation, and metadata.

Data Observability 52

Data Observability Data Quality Data Governance Data Pipeline 52

Pickl AI

SEPTEMBER 5, 2024

Unified Data Services: Azure Synapse Analytics combines big data and data warehousing, offering a unified analytics experience. Azure’s global network of data centres ensures high availability and performance, making it a powerful platform for Data Scientists to leverage for diverse data-driven projects.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Precisely

APRIL 3, 2023

Court documents and case dockets were stored on a mainframe system, where they were inaccessible to the public at large. Precisely helped court officials to implement a streaming data pipeline to replicate that information to a cloud data platform, where it was available for web developers to publish online.

ETL 52

ETL Analytics Analytics Database 52

Alation

APRIL 14, 2022

Data pipeline orchestration. Moving/integrating data in the cloud/data exploration and quality assessment. A cloud environment with such features will support collaboration across departments and across common data types, including csv, JSON, XML, AVRO, Parquet, Hyper, TDE, and more. Collaboration and governance.

Data Governance 59

Data Governance ML ML Cloud Data 59

DagsHub

AUGUST 23, 2024

It is particularly popular among data engineers as it integrates well with modern data pipelines (e.g., Source: [link] Monte Carlo is a code-free data observability platform that focuses on data reliability across data pipelines. It integrates well with modern data engineering pipelines (e.g.,

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Alation

JANUARY 17, 2023

Data ingestion/integration services. Data orchestration tools. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? What Are the Benefits of a Modern Data Stack?

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

phData

AUGUST 15, 2024

The hype around generative AI has shifted the industry narrative overnight from the big data era of “every company is a data company” to the new belief that “every company is an AI company.” This metric would be used to decide whether more or less documents are needed to provide relevant context.

AI 52

AI AI Data Engineering Data Engineering 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

SIMD describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously. SIMT describes processors that are able to operate on data vectors and arrays (as opposed to just scalars), and therefore handle big data workloads efficiently.

AWS 113

AWS ML ML Clustering 113

phData

OCTOBER 20, 2023

To support these diverse data sources, semi-structured data formats have become popular standards for transporting and storing data. What are Supported File Formats for Semi-structured Data Various semi-structured datasets, including JSON, Avro, Parquet, Orc, and XML, have emerged with the rise of big data and IoT.

Big Data 40

Big Data Big Data Database Hadoop 40

ODSC - Open Data Science

JANUARY 7, 2025

Classification techniques, such as image recognition and document categorization, remain essential for a wide range of industries. Soft Skills Technical expertise alone isnt enough to thrive in the evolving data science landscape. Employers increasingly seek candidates with strong soft skills that complement technical prowess.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

AWS Machine Learning Blog

OCTOBER 24, 2024

Large language models (LLMs) are very large deep-learning models that are pre-trained on vast amounts of data. One model can perform completely different tasks such as answering questions, summarizing documents, translating languages, and completing sentences. These indexes continuously accumulate documents.

AWS 115

AWS Data Pipeline Database Big Data 115

AWS Machine Learning Blog

NOVEMBER 19, 2024

We reuse the data pipelines described in this blog post. Clinical data The data is stored in CSV format as shown in the following table. Icons show each stage: document icons for DICOM files, S3 bucket symbol, lung CT scan images, segmented tumor view, and tabular data representing extracted features.

SQL 81

SQL Database Data Analysis Data Analysis 81