O'Reilly on Data
NOVEMBER 18, 2019
Highlights from the interview include: The biggest hurdle businesses face when implementing machine learning or AI solutions is cleaning and preparing unstructured data that exists across silos. Open source data and transfer learning are also enabling businesses to more easily move models into production and to achieve an ROI.
CIO Business Intelligence
NOVEMBER 22, 2024
Soumya Seetharam, CDIO at Corning, said the manufacturer has been on its data journey for a few years, with more than 70% of its business transaction data being ingested into a data platform. But that’s only structured data, she emphasized. I think driving down the data, we can come up with some kind of solution.”
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Corinium
APRIL 7, 2021
This brief explains how data virtualization, an advanced data integration and data management approach, enables unprecedented control over security and governance. In addition, data virtualization enables companies to access data in real time while optimizing costs and ROI.
CIO Business Intelligence
DECEMBER 10, 2024
Proving the ROI of AI can be elusive , but rushing to achieve it can prove costly. Improving data quality and integrating new data sources to enrich customer and prospect data are vital for applying AI in marketing and sales. Paul Boynton, co-founder and COO of Company Search Inc.,
Analytics Vidhya
SEPTEMBER 10, 2021
This article was published as a part of the Data Science Blogathon What is Image Segmentation? Image Segmentation helps to obtain the region of interest (ROI) from the image. It is the process of separating an image into different areas. The parts into which the image is divided are called Image Objects. It is done based […].
CIO Business Intelligence
SEPTEMBER 12, 2024
The first and most important step is to take a strategic approach, which means identifying the data being collected and stored while understanding how it ties into existing operations. This needs to work across both structured and unstructured data, including data held in physical documents.
O'Reilly on Data
FEBRUARY 11, 2020
They’re still struggling with the basics: tagging and labeling data, creating (and managing) metadata, managing unstructured data, etc. Nearly one-quarter of respondents work as data scientists or analysts (see Figure 1). An additional 7% are data engineers. Some other common data quality issues (Figure 4)—e.g.,
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