IBM Big Data Hub

MAY 19, 2023

According to the research, organizations are adopting cloud ERP models to identify the best alignment with their strategy, business development, workloads and security requirements. In addition, cloud ERP solutions enable SMEs to enhance their overall productivity by reducing manufacturing time.

Cloud 81

Cloud Unstructured data Customer Experience Manufacturing 81

IBM Big Data Hub

DECEMBER 19, 2023

Anomalies are not inherently bad, but being aware of them, and having data to put them in context, is integral to understanding and protecting your business. The challenge for IT departments working in data science is making sense of expanding and ever-changing data points.

Unstructured data 72

Unstructured data Artificial Intelligence Sales Manufacturing 72

IBM Big Data Hub

FEBRUARY 2, 2023

In addition, companies have complex data security requirements. However, over the past decade, a vast array of compliance and security standards, such as SOC2, PCI, HIPAA, and GDPR, have been introduced, and met by cloud providers.

Cloud 57

Cloud Analytics Unstructured data Compliance 57

IBM Big Data Hub

SEPTEMBER 19, 2022

Smart grids, which include components like sensors and smart meters, produce a wealth of telemetry data that can be used for multiple purposes, including: Identifying anomalies such as manufacturing defects or process deviations. Supply chain optimization (in manufacturing). Real-time operational dashboards.

Analytics 52

Analytics IoT Unstructured data Manufacturing 52

IBM Big Data Hub

FEBRUARY 14, 2024

Smart home devices such as the iRobot Roomba can navigate a home’s interior using computer vision and use data stored in memory to understand its progress. Clean up with predictive maintenance AI can be used for predictive maintenance by analyzing data directly from machinery to identify problems and flag required maintenance.

Artificial Intelligence 88

Artificial Intelligence Retail Unstructured data Insurance 88

IBM Big Data Hub

JULY 6, 2023

Other challenges include communicating results to non-technical stakeholders, ensuring data security, enabling efficient collaboration between data scientists and data engineers, and determining appropriate key performance indicator (KPI) metrics. appeared first on IBM Blog.

Data science 60

Data science Big data Analytics Mining 60

eDiscovery Daily

AUGUST 7, 2018

Now, Tom has written another terrific overview regarding pre-litigation considerations titled Preparing for Litigation Before it Happens that we’re happy to share on the eDiscovery Daily blog. IG, or as it’s also known data governance, is basically a set of rules and policies that have to do with a company’s data. Data access.

IT 31

IT Unstructured data Information governance Government 31