IBM Big Data Hub

NOVEMBER 29, 2023

For instance, if a business prioritizes accuracy in generating synthetic data, the resulting output may inadvertently include too many personally identifiable attributes, thereby increasing the company’s privacy risk exposure unknowingly.

Metrics 81

Metrics Machine Learning Statistics Risk 81

Smart Data Collective

AUGUST 26, 2021

Deep learning technology is changing the future of small businesses around the world. A growing number of small businesses are using deep learning technology to address some of their most pressing challenges. New advances in deep learning are integrated into various accounting algorithms.

Deep Learning 95

Deep Learning Finance Cost-Benefit Advertising 95

DataKitchen

APRIL 13, 2021

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix. Data breaks.

Testing 300

Testing Machine Learning Consulting Data Quality 300

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 117

Data Lake Unstructured Data Data Warehouse Data Quality 117

AWS Big Data

MARCH 1, 2023

The inability to accurately find and analyze data from disparate sources represents a potential efficiency killer for everyone from data scientists, medical researchers, academics, to financial and government analysts. Transform CSV to Parquet Raw CSV files are converted to Parquet data format with AWS Glue.

Data Lake 86

Data Lake Deep Learning Modeling Interactive 86

Domino Data Lab

JULY 22, 2019

By virtue of that, if you take those log files of customers interactions, you aggregate them, then you take that aggregated data, run machine learning models on them, you can produce data products that you feed back into your web apps, and then you get this kind of effect in business. That was the origin of big data.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

IBM Big Data Hub

AUGUST 1, 2022

2000 Deep Learning: . Deep learning attempts to mimic the human brain and helps with enabling systems in clustering data and making predictions with incredible accuracy. It has raised the bar for image recognition and even learning patterns for unstructured data. .

Unstructured Data 52

Unstructured Data Deep Learning Data Quality Data Architecture 52

Domino Data Lab

MARCH 3, 2019

Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise. O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). The data types used in deep learning are interesting.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

JUNE 23, 2019

It used deep learning to build an automated question answering system and a knowledge base based on that information. It is like the Google knowledge graph with all those smart, intelligent cards and the ability to create your own cards out of your own data. Now many people are using Spark.

Management 110

Management Machine Learning Experimentation Metrics 110

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. We would like to talk about data visualization and its role in the big data movement.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

CIO Business Intelligence

JANUARY 20, 2023

And modern object storage solutions, offer performance, scalability, resilience, and compatibility on a globally distributed architecture to support enterprise workloads such as cloud-native, archive, IoT, AI, and big data analytics. Protecting the data : Cyber threats are everywhere—at the edge, on-premises and across cloud providers.

Analytics 136

Analytics Key Performance Indicator Unstructured Data IoT 136

O'Reilly on Data

MARCH 24, 2020

You may picture data scientists building machine learning models all day, but the common trope that they spend 80% of their time on data preparation is closer to the truth. This definition of low-quality data defines quality as a function of how much work is required to get the data into an analysis-ready form.

Machine Learning 347

Machine Learning Statistics Data Quality Modeling 347