Data Virtualization

MAY 26, 2021

Data is becoming increasingly important for understanding markets and customer behaviors, optimizing operations, deriving foresights, and gaining a competitive advantage. Over the last decade, the explosion of structured and unstructured data as well as digital technologies in general, has enabled.

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Virtualization Industry Data Technology 80

Datavail

JULY 12, 2022

Considering the massive volume of structured data streaming into databanks every day, it’s almost shocking to learn that it represents only 10 to 20% of all available data. The other 80 to 90% is unstructured data , the type of data that doesn’t fit neatly into tables, rows, or columns.

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CIO

AUGUST 17, 2023

Coby adds that the immature regulatory and legal structures around using generative AI and large language models (LLM) need to be carefully considered, as does the tendency of current programs to hallucinate. AI can analyze large volumes of data in textual form to create new forms, summaries, and analyses of the data sets,” he says. “It

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Generative AI Artificial Inteligence ChatGPT Training 230

Linux Academy

JULY 9, 2019

“Big data” has slowly transitioned from a buzzword to a part of everyday life, but it’s still somewhat mysterious. What exactly is big data? Our new Big Data Fundamentals course offers a high-level overview of the types of big data, its architecture, and some main technologies that use it. Structured Data.

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AWS Machine Learning - AI

MARCH 4, 2024

Vision capabilities – Claude 3 models have been trained to understand structured and unstructured data across different formats, not just language, but also images, charts, diagrams, and more. For instance, pharmaceutical companies can query drug research papers alongside protein structure diagrams to accelerate discovery.

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Data Virtualization

JULY 21, 2021

The volume of data, both structured and unstructured, continues to grow exponentially, and organizations continue to struggle to leverage all of the data to make the best business decisions. The post Data Virtualization: A flexible, Agile, and Cost-Effective Solution appeared first on Data Virtualization blog.

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Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

Data 108

Data Architecture Analytics Government 108

Sunflower Lab

JULY 21, 2023

This blog explores the key differences between RPA and IPA, their capabilities, and their applications in the automation process. Finance RPA ensures efficient and accurate execution of financial operations by handling tasks like invoice processing, customer onboarding, data entry, etc. billion, reaching 51.35 billion in 2032.

Healthcare 52

Healthcare VR Budget Video 52

Datavail

DECEMBER 2, 2021

Snowflake took the market by storm when it introduced its innovative cloud-based data warehouse technology in 2014. It is one of the first data warehousing platforms offered as a software as a service (SaaS) product with storage, compute, and cloud services operating separately and billing as independent units. You Pick the Platform.

Data 98

Data Analytics Azure Storage 98

Cloudera

FEBRUARY 23, 2023

Solving this crisis can and should be supported by insights gained from the vast amounts of data available to healthcare providers and government agencies. With CDP, KMC was able to develop the aptly named Controlled Substance Analytics platform to leverage data analytics in the fight against opioid abuse and misuse.

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Analytics Data Healthcare Pharmaceuticals 76

Datavail

JULY 14, 2022

Streaming data is one such asset. It is constantly feeding corporate databanks with up-to-the-minute information, yet because its flow is transitory, the intelligence it offers isn’t available for use until after it’s been captured, cleaned, and integrated into standard data analysis programs. Static vs. Streaming Data.

Data 52

Data AWS Analytics Programming 52

Tandem

SEPTEMBER 12, 2023

This blog post will provide a balanced view of the advantages and disadvantages of microservice architecture for enterprise software systems. These services are structured around business functions and interact with each other through APIs and message queues. As a result, slower response times and reduced performance can occur.

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Microservices Architecture Weak Development Team Serverless 52

Coforge

SEPTEMBER 28, 2020

* field--node--title--blog-post.html.twig x field--node--title.html.twig * field--node--blog-post.html.twig * field--title.html.twig * field--string.html.twig * field.html.twig --> 4 Steps to Solve the Unstructured Data Problem. Unstructured Data. Characteristics of Unstructured Data.

Artificial Inteligence 40

Artificial Inteligence Data Artificial Intelligence Quality Assurance 40

Cloudera

APRIL 7, 2022

As a public sector leader, you don’t need the value of data explained to you. Simply collecting data isn’t enough anymore: government agencies must harness the value of that data in motion with an effective data strategy and platform. You already understand its importance to your vital missions. .

Government 90

Government Machine Learning Artificial Inteligence Analytics 90

Cloudera

DECEMBER 19, 2023

Innovations in AI-enabled data management in defense and intelligence communities also enable secure data sharing across the organization and with partners, optimizing data analysis and intelligence collaboration. Make sure to audit data regularly. Trust your data. Improve dataset quality. Trust your enterprise AI.

Artificial Inteligence 86

Artificial Inteligence Generative AI Government Technical Review 86

Cloudera

MAY 18, 2022

By leveraging data, analytics, and automation, a company can gain a better understanding of where it is and where it needs to go. That means developing scenarios in which AI can boost efficiency, productivity, and process optimization through AI-enabled data analytics and automation. . Will the data have other uses? Bottom line.

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Cloudera

AUGUST 4, 2021

In fact, McKinsey points to a 50% reduction in downtime and a 40% reduction in maintenance costs when using IoT and data analytics to predict and prevent breakdowns. The key is active and ongoing monitoring of prognostic health data. Cloudera is foundational in how we track and govern our data.” .

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IoT Machine Learning Artificial Inteligence Government 98

Cloud That

NOVEMBER 17, 2022

AWS Glue is a robust, cost-effective ETL (extraction, transformation, and loading) service used to clean, enhance, categorize, and securely move data between data streams and repositories. AWS Glue is a cloud service that prepares data for analysis. You can work with semi-structured or grouped data using AWS Glue.

AWS 75

AWS Data Serverless Cloud 75

Perficient

DECEMBER 12, 2023

Introduction In this blog, we will show you how to build a conversational search application that can interact with Azure Cognitive Search (ACS) and retrieve relevant content from a web-scraped index by asking natural language questions, requesting for summary information, and using vector search.

Artificial Inteligence 52

Artificial Inteligence Azure Applications Generative AI 52

Tandem

JANUARY 24, 2023

Undertaking any of these projects means having to plan a data migration. Moving data from one database type to another such as SQL to NoSQL will clearly have implications but even a relational database migration from a row to columnar database also has implications for the data.

Data 52

Data Testing AWS Storage 52

Apps Associates

MAY 18, 2021

Background: When data lakes first came on the scene they were usually on-premises Hadoop clusters. Such systems could store any kind of data in its raw format at massive scale. Performing analytics on the data was possible but took a long time and was mostly done in batch (using map reduce routines written in Java).

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Perficient

AUGUST 8, 2023

I have read several articles that explain that the Data Lake, Data Warehouse, and Data Lakehouse are different repositories and that you may need several or all of them. In this post, I will explain why I believe you don’t need anything other than a modern Data Lake. You can find my three-part series, here.

Data 52

Data Artificial Inteligence Artificial Intelligence Serverless 52

Cloudera

JANUARY 28, 2022

As I meet with our customers, there are always a range of discussions regarding the use of the cloud for financial services data and analytics. Customers vary widely on the topic of public cloud – what data sources, what use cases are right for public cloud deployments – beyond sandbox, experimentation efforts.

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Cloud Data Government Strategy 111

Cloudera

DECEMBER 11, 2020

These include the use of more data sources to gain insights and how cloud technologies can assist with digital transformation goals to be more agile and achieve objectives more quickly. Data Variety. Insurance and finance are two industries that rely on measuring risk with historical data models. Insurance .

Data 92

Data Insurance Machine Learning Artificial Inteligence 92

Cloudera

JULY 29, 2021

Securely protecting healthcare data is critical for your organization’s success, whether data is ingested, streamed and stored in a data platform that runs in the public, private or hybrid cloud. Public, private, hybrid or on-premise data management platform. Security and governance in a hybrid environment. Meet with us.

Healthcare 100

Healthcare Data Government Analytics 100

Cloudera

MARCH 28, 2023

Today’s healthcare is driven as much by the promise of emerging technologies centered on data processing and advanced analytics as by developing new and specialized drugs. Precision healthcare leverages data and AI-powered advanced analytics to predict and prevent disease and to identify the most effective treatments for each patient.

Healthcare 66

Healthcare Data Machine Learning Artificial Inteligence 66

Cloudera

FEBRUARY 4, 2021

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. End-to-end Data Lifecycle. Shared Data Experience (SDX).

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Technical Review Marketing Technology Data 88

Cloudera

OCTOBER 28, 2020

By using data to listen to their customers better. The most innovative companies use data and analytics to offer appropriate products and services. To start, they look to traditional financial services data, combining and correlating account activity, borrowing history, core banking, investments, and call center data.

Data 69

Data Analytics Banking Machine Learning 69

Coforge

APRIL 28, 2020

Whether you’ve been using a BPM tool for 5+ years or just starting out, you’ve probably heard about “unstructured data”. Here’s how in 4 steps: Extract Tables: When you think of extracting data from documents, what is the first example you think of? There’s a second side to unstructured data that’s often ignored.

Quality Assurance 52

Quality Assurance Machine Learning Artificial Inteligence Applications 52

Cloud That

NOVEMBER 17, 2022

Modern technology has solved this problem to a large extent and data can be extracted from structured forms without human touch. In other cases, however, data is received from a wide variety of unstructured documents without any rhyme or reason to the way the information is presented. About AWS Textract. textract-lambda).

AWS 75

AWS Lambda Data Machine Learning 75

Datavail

JULY 7, 2022

Unstructured data. Legacy analytics infrastructure was often designed for an era where the majority of enterprise data was structured (i.e. data that belongs in a row-column tabular database). Multiple studies estimate that unstructured data could make up as much as 80 to 90 percent of all information.

Analytics 52

Analytics Artificial Inteligence Cloud Artificial Intelligence 52

Cloudera

OCTOBER 28, 2021

I’ve had the pleasure to participate in a few Commercial Lines insurance industry events recently and as a prior Commercial Lines insurer myself, I am thrilled with the progress the industry is making using data and analytics. Commercial Lines truly is an “uber industry” with respect to data. A Long, Long Time Ago.

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Insurance Data Analytics Industry 95

Prisma Clud

NOVEMBER 21, 2023

Enterprises often interpret a data security mandate as identifying configuration issues or vulnerabilities in their data infrastructure. To improve security posture, though, the scope of data security activities must be to protect sensitive data assets such as customer information, trade secrets, financial information or patents.

Data 52

Data Policies Software Review Compliance 52

Cloudera

DECEMBER 3, 2020

Cindy is an exceptional female leader and we hope this blog gives you insight into the great work Cindy is doing with the Industry Solutions team! . I came to the organization because of my interest in data & analytics specific to the insurance industry. Reference Blog. What’s your morning pick me up drink?

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Industry Insurance Healthcare Analytics 53

Cloudera

SEPTEMBER 17, 2020

Today’s data tool challenges. By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. .

Data 81

Data How To Technical Review Systems Review 81

Cloudera

JANUARY 5, 2021

In today’s retail environment, retailers realize that building demand forecasts simply based upon historical transaction, promo, and pricing data alone is not good enough. Data today has a shelf life much like produce and needs to be updated in real-time to be relevant. Data 100 days old might as well be 100 years old.

Agile 91

Agile Retail Analytics Enterprise 91

Cloudera

NOVEMBER 16, 2020

Use the Data Available. This requires a lot of data, a variety of data, and advanced analytic capabilities. Third-party data such as location, social media, obituaries, repair costs, and others help in faster identifying suspicious claims or applications.

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