IBM Journey to AI blog

JULY 3, 2024

Align your data strategy to a go-forward architecture, with considerations for existing technology investments, governance and autonomous management built in. Look to AI to help automate tasks such as data onboarding, data classification, organization and tagging.

Metadata 113

Metadata Data Quality AI AI 113

IBM Journey to AI blog

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

ESG 264

ESG Metadata AI AI 264

IBM Journey to AI blog

OCTOBER 14, 2024

Internally, we’ve implemented a marketing-automation use case where IBM’s brand guidelines and examples were ingested to generate new marketing content and curate it for consistent quality and tone. Similarly, the proliferation of agents will infuse data into an exploding volume and variety of automated workflows.

Business Intelligence 219

Business Intelligence AI AI Automation 219

Marktechpost

JUNE 5, 2024

In addition, organizations that rely on data must prioritize data quality review. Data profiling is a crucial tool. For evaluating data quality. Data profiling gives your company the tools to spot patterns, anticipate consumer actions, and create a solid data governance plan.

Data Quality 115

Data Quality Metadata Data Integration ETL 115

AWS Machine Learning Blog

FEBRUARY 27, 2024

Axfood has a structure with multiple decentralized data science teams with different areas of responsibility. Together with a central data platform team, the data science teams bring innovation and digital transformation through AI and ML solutions to the organization. Workflow B corresponds to model quality drift checks.

Machine Learning 134

Machine Learning DevOps Data Scientist Data Quality 134

TheSequence

JULY 5, 2023

Not surprisingly, data quality and drifting is incredibly important. Many data drift error translates into poor performance of ML models which are not detected until the models have ran. A recent study of data drift issues at Uber reveled a highly diverse perspective.

Data Drift 52

Data Drift Data Quality Metadata Data Platform 52

Unite.AI

JANUARY 18, 2024

AI has proven to be useful in task automation and process optimization, as well as in promoting creativity and innovation. However, as data complexity and diversity continue to increase, there is a growing need for more advanced AI models that can comprehend and handle these challenges effectively.

Computer Vision 264

Computer Vision OpenAI Artificial Intelligence Artificial Intelligence 264

Pickl AI

OCTOBER 6, 2024

This phase is crucial for enhancing data quality and preparing it for analysis. Transformation involves various activities that help convert raw data into a format suitable for reporting and analytics. Normalisation: Standardising data formats and structures, ensuring consistency across various data sources.

ETL 52

ETL Data Quality Data Integration Big Data 52

The MLOps Blog

MARCH 15, 2023

As the volume of data keeps increasing at an accelerated rate, these data tasks become arduous in no time leading to an extensive need for automation. This is what data processing pipelines do for you. Let’s understand how the other aspects of a data pipeline help the organization achieve its various objectives.

ETL 59

ETL Categorization Automation Data Integration 59

AWS Machine Learning Blog

NOVEMBER 15, 2023

In order analyze the calls properly, Principal had a few requirements: Contact details: Understanding the customer journey requires understanding whether a speaker is an automated interactive voice response (IVR) system or a human agent and when a call transfer occurs between the two.

Data Ingestion 126

Data Ingestion Metadata NLP Data Scientist 126

Flipboard

MARCH 22, 2023

In this post, we show how to configure a new OAuth-based authentication feature for using Snowflake in Amazon SageMaker Data Wrangler. Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. Data Wrangler creates the report from the sampled data.

IDP 123

IDP Data Scientist Categorization Data Quality 123

Pickl AI

JUNE 23, 2023

Data Annotation In many AI applications, data annotation is necessary to label or tag the data with relevant information. Data annotation can be done manually or using automated techniques. Training Data Selection A critical aspect of data-centric AI is selecting the right subset of data for training the AI models.

Continuous Learning 52

Continuous Learning Data Quality AI AI 52

ODSC - Open Data Science

OCTOBER 20, 2023

From Data Collection to ML Model Deployment in Less Than 30 Minutes Hudson Buzby | Qwak Solution Architect | Qwak Explore Qwak MLOps Platform, a comprehensive platform tailored to empower data scientists, engineers, and organizations.

NLP 52

NLP Data Science Machine Learning Data Analysis 52

Marktechpost

JULY 17, 2023

Consider retail automation in the shape of an Amazon Go location, where a computer vision system monitors shoppers to ensure no one leaves with any five-finger discounts. To educate self-driving cars on how to avoid killing people, the business concentrates on some of the most challenging use cases for its synthetic data platform.

Machine Learning 52

Machine Learning Data Scientist Computer Vision Deep Learning 52

AWS Machine Learning Blog

AUGUST 4, 2023

Use the newly launched SageMaker provided project template for Salesforce Data Cloud integration to streamline implementing the preceding steps by providing the following templates: An example notebook showcasing data preparation, building, training, and registering the model. Choose clone repo for both notebooks.

ML 90

ML Categorization AI AI 90

Snorkel AI

JUNE 9, 2023

Snorkel AI wrapped the second day of our The Future of Data-Centric AI virtual conference by showcasing how Snorkel’s data-centric platform has enabled customers to succeed, taking a deep look at Snorkel Flow’s capabilities, and announcing two new solutions.

Large Language Models 52

Large Language Models Data Scientist Machine Learning Computer Vision 52

Snorkel AI

JUNE 9, 2023

Snorkel AI wrapped the second day of our The Future of Data-Centric AI virtual conference by showcasing how Snorkel’s data-centric platform has enabled customers to succeed, taking a deep look at Snorkel Flow’s capabilities, and announcing two new solutions.

Large Language Models 52

Large Language Models Data Scientist Machine Learning Computer Vision 52

IBM Journey to AI blog

JULY 27, 2023

One example of this is reducing labor burdens by automating ticket assistance through IT operations. Precisely conducted a study that found that within enterprises, data scientists spend 80% of their time cleaning, integrating and preparing data , dealing with many formats, including documents, images, and videos.

Generative AI 188

Generative AI Chatbots AI AI 188

Pickl AI

JUNE 11, 2024

Self-Service Analytics User-friendly interfaces and self-service analytics tools empower business users to explore data independently without relying on IT departments. Best Practices for Maximizing Data Warehouse Functionality A data warehouse, brimming with historical data, holds immense potential for unlocking valuable insights.

ETL 52

ETL Data Mining Actionable Intelligence Data Integration 52

The MLOps Blog

MARCH 21, 2023

It should be able to version the project assets of your data scientists, such as the data, the model parameters, and the metadata that comes out of your workflow. Automation You want the ML models to keep running in a healthy state without the data scientists incurring much overhead in moving them across the different lifecycle phases.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

IBM Journey to AI blog

AUGUST 4, 2023

It’s often described as a way to simply increase data access, but the transition is about far more than that. When effectively implemented, a data democracy simplifies the data stack, eliminates data gatekeepers, and makes the company’s comprehensive data platform easily accessible by different teams via a user-friendly dashboard.

Machine Learning 189

Machine Learning Metadata AI AI 189