Snowflake

OCTOBER 26, 2023

Gen AI can also analyze unstructured data sets, such as clinical notes, diagnostic imaging and recordings and provide evidence-based recommendations. An inconsistent data set introduces biases and inaccuracies, which can have profound consequences for clinicians or scientists using an AI model for patient health.

Healthcare 85

Healthcare Unstructured Data High Quality Data Medical 85

Snowflake

JULY 25, 2024

Snowflake Cortex Search, a fully managed search service for documents and other unstructured data, is now in public preview. Solving the challenges ofbuilding high-quality RAG applications From the beginning, Snowflake’s mission has been to empower customers to extract more value from their data.

Unstructured Data 52

Unstructured Data Metadata Government Database 52

Snowflake

JANUARY 25, 2024

It’s essential for organizations to leverage vast amounts of structured and unstructured data for effective generative AI (gen AI) solutions that deliver a clear return on investment. Data security and governance aren’t the only reasons leading organizations will take this approach.

Healthcare 91

Healthcare Hospitality Electronics Medical 91

Cloudera

DECEMBER 11, 2020

The Data Security and Governance category, at the annual Data Impact Awards, has never been so important. Finally, throw in the constant stream of cyberthreats out there and it’s clear that protecting your enterprise’s data is vital. Toolsets and strategies have had to shift to ensure controlled access to data.

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

Snowflake

JULY 9, 2024

To better understand a customer’s current data reality we ask a series of questions: Do you have access to all of your internal data? Have you unlocked data from existing applications, systems or business unit silos? Have you transformed your unstructured data into structured, usable data?

Government 84

Government Education Data Governance Unstructured Data 84

Cloudera

SEPTEMBER 12, 2022

Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. And second, for the data that is used, 80% is semi- or unstructured. Both obstacles can be overcome using modern data architectures, specifically data fabric and data lakehouse.

Unstructured Data 75

Unstructured Data Data Lake Data Architecture Data 75

RandomTrees

SEPTEMBER 27, 2024

This eliminates the need to make multiple copies of data assets. Unified data platform: One Lake provides a unified platform for all data types, including structured, semi-structured, and unstructured data.

Database-centric 52

Database-centric Pipeline-centric IT BI 52

Cloudera

JULY 29, 2021

We also expect topics such as interoperability, social determinants of health, advanced analytics, economics, security and governance, and leadership to take top billing at the conference this year. . Security and governance in a hybrid environment. Public, private, hybrid or on-premise data management platform.

Healthcare 102

Healthcare Unstructured Data Government Machine Learning 102

Snowflake

JUNE 5, 2024

Additionally, upon implementing robust data security controls and meeting regulatory requirements, businesses can confidently integrate AI while meeting compliance standards. By using Cortex, enterprises can bring AI directly to the governed data to quickly extend access and governance policies to the models.

Coding 89

Coding Building Management Government 89

Cloudera

NOVEMBER 17, 2022

We needed a solution to manage our data at scale, to provide greater experiences to our customers. With Cloudera Data Platform, we aim to unlock value faster and offer consistent data security and governance to meet this goal. Aqeel Ahmed Jatoi, Lead – Architecture, Governance and Control, Habib Bank Limited.

Banking 85

Banking Management Data Lake Professional Services 85

Cloudera

OCTOBER 28, 2020

To start, they look to traditional financial services data, combining and correlating account activity, borrowing history, core banking, investments, and call center data. However, the bank’s federated data marts gave each business only enough data to substantiate its own business.

Unstructured Data 73

Unstructured Data Banking Machine Learning Media 73

Precisely

MAY 13, 2024

The right data integration solution helps you streamline operations, enhance data quality, reduce costs, and make better data-driven decisions. It synthesizes all the metadata around your organization’s data assets and arranges the information into a simple, easy-to-understand format.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Knowledge Hut

APRIL 23, 2024

With the advent of technology and the arrival of modern communications systems, computer science professionals worldwide realized big data size and value. As big data evolves and unravels more technology secrets, it might help users achieve ambitious targets. Top 10 Disadvantages of Big Data 1.

Big Data 52

Big Data Media Government Big Data Skills 52

Knowledge Hut

APRIL 25, 2024

Data Governance Data governance is the process of ensuring that data is trustworthy, accurate, available, and usable. It describes the actions people must take, the rules they must follow, and the technology that will support them throughout the data life cycle.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Cloudera

JUNE 22, 2023

It ensures compliance with regulatory requirements while shifting non-sensitive data and workloads to the cloud. Its built-in intelligence automates common data management and data integration tasks, improves the overall effectiveness of data governance, and permits a holistic view of data across the cloud and on-premises environments.

Data Cleanse 65

Data Cleanse Data Governance Unstructured Data Cloud Storage 65

Knowledge Hut

JULY 24, 2023

Cloud migration has several benefits, including improved data accessibility, more straightforward data backup and disaster recovery, and lower infrastructure expenses. They are probably the best option for contemporary applications that need real-time data processing, great scalability, and flexibility.

Database 52

Database NoSQL Management Relational Database 52

Towards Data Science

DECEMBER 4, 2023

We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Data Lake A data lake would serve as a repository for raw and unstructured data generated from various sources within the Formula 1 ecosystem: telemetry data from the cars (e.g.

Data Engineering 82

Data Engineering Data Engineer Engineering Data Lake 82

Monte Carlo

APRIL 24, 2023

One weakness of the data lake architecture was the need to “bolt on” a data store such as Hive or Glue. This was largely overcome when Databricks announced their Unity Catalog feature which fully integrates those metastores along with other partnering data catalog and data security technologies.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Monte Carlo

JUNE 27, 2023

The new service combines technology from Applica, which Snowflake acquired in 2022, with a proprietary large language model to extract and better understand the unstructured data (text) within documents. Some governance stuff New governance features got quick lip service almost like an announcmenet amuse-bouche.

Data Lake 59

Data Lake Government SQL Unstructured Data 59

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . ModelOp — Governs, monitors, and orchestrates models across the enterprise. Meta-Orchestration .

Consulting 121

Consulting Machine Learning Data Science Data Pipeline 121

Knowledge Hut

MARCH 28, 2024

Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance. Develop data models, data governance policies, and data integration strategies. GDPR, HIPAA), and industry standards.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Databand.ai

JULY 19, 2023

Unlike the traditional Extract, Transform, Load (ETL) process, where transformations are performed before the data is loaded into the data warehouse, in ELT, transformations are performed after the data is loaded. Implementing Strong Data Governance Measures Implementing strong data governance measures is crucial in ELT.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

AltexSoft

AUGUST 29, 2023

Unstructured data sources. This category includes a diverse range of data types that do not have a predefined structure. Examples of unstructured data can range from sensor data in the industrial Internet of Things (IoT) applications, videos and audio streams, images, and social media content like tweets or Facebook posts.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

APRIL 20, 2023

Enroll in Knowledge Hut's comprehensive course on Data Science today. Cybersecurity vs Data Science [Head-to-Head Comparison] Cybersecurity and data science are well-paying and in-demand jobs that need a thorough grasp of technology and data security.

Data Science 52

Data Science Computer Science Healthcare Recruitment 52

AltexSoft

FEBRUARY 11, 2023

If KPI goals are not met, a data architect recommends solutions (including new technologies) to improve the existing framework. Besides, it’s up to this specialist to guarantee compliance with laws, regulations, and standards related to data. This privacy law must be kept in mind when building data architecture.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

APRIL 23, 2024

Sentiment Analysis and Natural Language Processing (NLP): AI and ML algorithms can process and analyze unstructured data, like text and speech, to better understand consumer sentiments. This entails constant surveillance, threat detection, and the adoption of strict security procedures all along the data lifecycle.

Big Data 52

Big Data Recruitment Retail Transportation 52

Knowledge Hut

SEPTEMBER 22, 2023

To provide their customers with scalable solutions, businesses rely on the expertise and abilities of data engineers. Additionally, as more companies use data to inform their decisions, data security will become even more important. How Long Does Microsoft Azure Data Engineer Certification Take?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudera

AUGUST 20, 2021

It is both the superior technical characteristics of each individual data experience and the cohesive choreography between them that make CDP the ideal data platform for complex data products that include multiple stages of analytical processing to deliver differentiated value propositions.

Data Warehouse 97

Data Warehouse Data Cloud Architecture 97

Knowledge Hut

JUNE 23, 2023

Data warehousing to aggregate unstructured data collected from multiple sources. Data architecture to tackle datasets and the relationship between processes and applications. Step 3 - How to Choose Project Management Courses for Data Engineer Learning Path? What’s the Demand for Data Engineers?

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Knowledge Hut

NOVEMBER 7, 2023

Every day, enormous amounts of data are collected from business endpoints, cloud apps, and the people who engage with them. Cloud computing enables enterprises to access massive amounts of organized and unstructured data in order to extract commercial value. This ensures the backup procedure and data security.

Cloud Computing 98

Cloud Computing Cloud Amazon Web Services Entertainment 98

AltexSoft

NOVEMBER 23, 2021

This often results in data inconsistencies and duplications as users demand more data views. Security and governance issues exist as sometimes sensitive data can’t be moved into the cloud or a centralized store, remaining in its native location. Enhanced data security and governance.

Process 69

Process Data Lake Metadata Data Warehouse 69

Knowledge Hut

JANUARY 30, 2024

Structured Data: Structured data sources, such as databases and spreadsheets, often require extraction to consolidate, transform, and make them suitable for analysis. Unstructured Data: Unstructured data, like free-form text, can be challenging to work with but holds valuable insights.

ETL Tools 52

ETL Tools Database-centric Data Mining Raw Data 52

Edureka

FEBRUARY 7, 2023

They should also be comfortable working with a variety of data sources and types and be able to design and implement data pipelines that can handle structured, semi-structured, and unstructured data.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Knowledge Hut

MARCH 26, 2024

Extensive experience in enterprise architecture, solution design, and IT governance. Responsibilities: Define data architecture strategies and roadmaps to support business objectives and data initiatives. Design data models, schemas, and storage solutions for structured and unstructured data.

Amazon Web Services 52

Amazon Web Services Google Cloud Computer Science AWS 52

ProjectPro

JANUARY 19, 2022

Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

AltexSoft

NOVEMBER 10, 2021

Traditional data warehouse platform architecture. Key data warehouse limitations: Inefficiency and high costs of traditional data warehouses in terms of continuously growing data volumes. Inability to handle unstructured data such as audio, video, text documents, and social media posts.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

OCTOBER 20, 2021

On that note, what is AI governance? AI Governance is a necessary evil. The four guideposts of AI Governance are as follows: Integrity The integrity and validity of the algorithm have to be justified by analyzing decision lineage and justification of what micro-decisions lead to the final output.

Machine Learning 52

Machine Learning Algorithm Data Science Government 52