Pickl AI

APRIL 14, 2023

Falling into the wrong hands can lead to the illicit use of this data. Hence, adopting a Data Platform that assures complete data security and governance for an organization becomes paramount. In this blog, we are going to discuss more on What are Data platforms & Data Governance.

Data Platform 52

Data Platform Data Integration Data Ingestion Automation 52

Unite.AI

OCTOBER 14, 2024

Skip Levens is a product leader and AI strategist at Quantum, a leader in data management solutions for AI and unstructured data. The company’s approach allows businesses to efficiently handle data growth while ensuring security and flexibility throughout the data lifecycle.

ML 195

ML Data Ingestion Data Analysis Machine Learning 195

IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 130

Data Quality Metadata ETL Big Data 130

Unite.AI

JUNE 4, 2024

However, the risk is not significant given Google Cloud's growth, broad data and infrastructure product portfolio and investment in Gen AI. A deep understanding of the cloud platform. We know Google Cloud inside and out, including key areas like data cloud, machine learning, AI, and Kubernetes.

Data Ingestion 130

Data Ingestion Data Platform Machine Learning Generative AI 130

Snorkel AI

JANUARY 8, 2025

In todays fast-paced AI landscape, seamless integration between data platforms and AI development tools is critical. At Snorkel, weve partnered with Databricks to create a powerful synergy between their data lakehouse and our Snorkel Flow AI data development platform. Sign up here!

AI Developer 52

AI Developer AI Development Data Ingestion LLM 52

AWS Machine Learning Blog

FEBRUARY 27, 2024

In this post, we share how Axfood, a large Swedish food retailer, improved operations and scalability of their existing artificial intelligence (AI) and machine learning (ML) operations by prototyping in close collaboration with AWS experts and using Amazon SageMaker. This is a guest post written by Axfood AB.

Machine Learning 137

Machine Learning DevOps Data Scientist Data Quality 137

AWS Machine Learning Blog

NOVEMBER 15, 2023

Solution overview After extensive research, the Principal team finalized AWS Contact Center Intelligence (CCI) solution s, which empower companies to improve customer experience and gain conversation insights by adding AI capabilities to third-party on-premises and cloud contact centers.

Data Ingestion 117

Data Ingestion Metadata NLP Data Scientist 117

AWS Machine Learning Blog

DECEMBER 18, 2023

In this post, we will explore the potential of using MongoDB’s time series data and SageMaker Canvas as a comprehensive solution. MongoDB Atlas MongoDB Atlas is a fully managed developer data platform that simplifies the deployment and scaling of MongoDB databases in the cloud.

Data Extraction 121

Data Extraction Data Ingestion ML Machine Learning 121

Pickl AI

DECEMBER 16, 2024

Whether you aim for comprehensive data integration or impactful visual insights, this comparison will clarify the best fit for your goals. Key Takeaways Microsoft Fabric is a full-scale data platform, while Power BI focuses on visualising insights. Its strength lies in visualising and analysing data rather than managing it.

ETL 52

ETL Data Ingestion Data Integration Machine Learning 52

AWS Machine Learning Blog

MARCH 29, 2023

Data ingestion HAYAT HOLDING has a state-of-the art infrastructure for acquiring, recording, analyzing, and processing measurement data. Two types of data sources exist for this use case. Digital Transformation, OT Security and Data & AI projects.

ML 98

ML Machine Learning Algorithm Data Scientist 98

The MLOps Blog

JANUARY 26, 2024

Keeping track of how exactly the incoming data (the feature pipeline’s input) has to be transformed and ensuring that each model receives the features precisely how it saw them during training is one of the hardest parts of architecting ML systems. Batch ML systems run on a schedule or are triggered when a new batch of data arrives.

Machine Learning 72

Machine Learning Metadata ML Python 72

Pickl AI

OCTOBER 10, 2024

Its drag-and-drop interface makes it user-friendly, allowing data engineers to build complex workflows without extensive coding knowledge. Nifi excels in data ingestion, routing, transformation, and system-to-system data flow management.

ETL 52

ETL Data Quality Business Intelligence Machine Learning 52

The MLOps Blog

MARCH 15, 2023

A typical data pipeline involves the following steps or processes through which the data passes before being consumed by a downstream process, such as an ML model training process. Data Ingestion : Involves raw data collection from origin and storage using architectures such as batch, streaming or event-driven.

ETL 59

ETL Categorization Data Integration Automation 59

Pickl AI

JUNE 29, 2023

Advantages of Using Splunk Real-time Visibility One of the significant advantages of Splunk is its ability to provide real-time data visibility. Thus, it lets users gain insights from vast data in real time. Additionally, it also supports a host of data formats. Thereby enabling faster decision-making and problem-solving.

Big Data 52

Big Data DevOps Data Analysis Machine Learning 52

ODSC - Open Data Science

JULY 19, 2023

Data Estate: This element represents the organizational data estate, potential data sources, and targets for a data science project. Data Engineers would be the primary owners of this element of the MLOps v2 lifecycle. The Azure data platforms in this diagram are neither exhaustive nor prescriptive.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

ODSC - Open Data Science

SEPTEMBER 29, 2023

Arjuna Chala, associate vice president, HPCC Systems For those not familiar with the HPCC Systems data lake platform, can you describe your organization and the development history behind HPCC Systems? They were interested in creating a data platform capable of managing a sizable number of datasets.

Big Data 52

Big Data ETL Data Science Data Ingestion 52

The MLOps Blog

MARCH 12, 2024

Tools range from data platforms to vector databases, embedding providers, fine-tuning platforms, prompt engineering, evaluation tools, orchestration frameworks, observability platforms, and LLM API gateways. LLMOps is key to turning LLMs into scalable, production-ready AI tools.

Prompt Engineering 52

Prompt Engineering Prompt Engineer Large Language Models LLM 52

The MLOps Blog

MARCH 21, 2023

” — Conor Murphy , Lead Data Scientist at Databricks, in “Survey of Production ML Tech Stacks” at the Data+AI Summit 2022 Your team should be motivated by MLOps to show everything that goes into making a machine learning model, from getting the data to deploying and monitoring the model.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

Bugra Akyildiz

FEBRUARY 24, 2024

Responsible AI Development: Phi-2 highlights the importance of considering responsible development practices when building large language models. Streaming data platforms: Apache Kafka and Apache Flink enable real-time ingestion and processing of user actions, clickstream data, and product catalogs, feeding fresh data to the models.

Large Language Models 52

Large Language Models LLM Data Ingestion Neural Network 52

TransOrg Analytics

SEPTEMBER 24, 2024

Google Data Studio: Turn data into informative dashboards and reports. Data & ML/LLM Ops on GCP Vertex AI: End-to-end platform to build, deploy, and scale ML models. Natural Language AI: Analyze and understand text data for LLM applications.

ETL 52

ETL LLM Data Ingestion Automation 52

TransOrg Analytics

SEPTEMBER 24, 2024

Google Data Studio: Turn data into informative dashboards and reports. Data & ML/LLM Ops on GCP Vertex AI: End-to-end platform to build, deploy, and scale ML models. Natural Language AI: Analyze and understand text data for LLM applications.

ETL 52

ETL LLM Data Ingestion Automation 52

Flipboard

NOVEMBER 27, 2024

In this post, we show you how to integrate the popular Slack messaging service with AWS generative AI services to build a natural language assistant where business users can ask questions of an unstructured dataset. The RAG workflow consists of two key components: data ingestion and text generation.

Generative AI 142

Generative AI Data Ingestion AI AI 142