Snowflake

OCTOBER 26, 2023

Realistic synthetic data created at scale, expediting research in rare under-addressed disease areas. These are just a few examples of how generative AI and large language models (LLMs) are transforming the healthcare and life sciences (HCLS) industry. Generative AI applications in HCLS According to a recent KPMG survey , 65% of U.S.

Healthcare 105

Healthcare Unstructured Data High Quality Data Insurance 105

Snowflake

SEPTEMBER 27, 2023

From improving patient outcomes to increasing clinical efficiencies, better access to data is helping healthcare organizations deliver better patient care. But all of this important data is often siloed and inaccessible or in hard-to-process formats, such as DICOM imaging, clinical notes or genomic sequencing.

Healthcare 104

Healthcare Accessible Accessibility Hospitality 104

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. Structure for unstructured data sources such as clinical & physician notes, photos, etc. Be The Change.

Healthcare 102

Healthcare Unstructured Data Government Machine Learning 102

Towards Data Science

DECEMBER 16, 2024

And over the last 24 months, an entire industry has evolved to service that very visionincluding companies like Tonic that generate synthetic structured data and Gretel that creates compliant data for regulated industries like finance and healthcare. But is synthetic data a long-term solution? Probablynot.

Unstructured Data 80

Unstructured Data Data Food Data Engineer 80

Snowflake

APRIL 16, 2025

This major enhancement brings the power to analyze images and other unstructured data directly into Snowflakes query engine, using familiar SQL at scale. Unify your structured and unstructured data more efficiently and with less complexity. Introducing Cortex AI COMPLETE Multimodal , now in public preview.

Data Analysis 61

Data Analysis Unstructured Data Manufacturing Retail 61

ProjectPro

JUNE 6, 2025

ETL for IoT - Use ETL to analyze large volumes of data IoT devices generate. Real-World ETL Use Cases and Applications Across Industries This blog discusses the numerous ETL use cases in various industries, including finance, healthcare, and retail.

BI 45

BI ETL Tools Retail Healthcare 45

ProjectPro

JUNE 6, 2025

Besides extracting structured information with enhanced contextual understanding, the following are the advantages of using a Knowledge graph for RAG systems: Structured graphs reduce the risk of hallucinations by providing factually correct, linked data rather than ambiguous textual chunks. Optimal for general unstructured data.

Building 52

Building Unstructured Data Database Datasets 52

ProjectPro

JUNE 6, 2025

He suggests one should start by understanding the crucial distinction between structured and unstructured data—it's the cornerstone. For those venturing into data engineering, structured data is your launchpad. Consider this advice as your compass through the diverse roles in data science.

Data Science 52

Data Science Unstructured Data Portfolio Healthcare 52

Teradata

JUNE 11, 2025

A key part of that ecosystem is the NVIDIA Enterprise AI Factory validated design —a validated design optimized for building and deploying AI agents across industries like finance, healthcare, and government. We’re excited to share that Teradata’s Enterprise Vector Store is included as part of this validated design.

Designing 52

Designing Unstructured Data Finance Media 52

Snowflake

FEBRUARY 6, 2024

An end-user-facing data catalog or marketplace can improve discoverability and access. Transform unstructured data to expand available internal data. To ensure that all data is made available, organizations must adopt tools to transform unstructured data into usable formats.

Unstructured Data 126

Unstructured Data Retail Data Manufacturing 126

Edureka

MAY 8, 2025

These are the ways that data engineering improves our lives in the real world. The field of data engineering turns unstructured data into ideas that can be used to change businesses and our lives. Data engineering can be used in any way we can think of in the real world because we live in a data-driven age.

Data Engineer 52

Data Engineer Data Engineering Engineering Telecommunication 52

ProjectPro

JUNE 6, 2025

The volume and the variety of data captured have also rapidly increased, with critical system sources such as smartphones, power grids, stock exchanges, and healthcare adding more data sources as the storage capacity increases. Why do you need a Data Ingestion Layer in a Data Engineering Project? application logs).

Data Ingestion 45

Data Ingestion Data Engineer Data Engineering Project 45

phData: Data Engineering

NOVEMBER 1, 2024

In an effort to better understand where data governance is heading, we spoke with top executives from IT, healthcare, and finance to hear their thoughts on the biggest trends, key challenges, and what insights they would recommend. The technology for metadata management, data quality management, etc., is fairly advanced.

Government 52

Government Data Governance Finance Metadata 52

Snowflake

APRIL 8, 2024

The list of Top 10 semi-finalists is a perfect example: we have use cases for cybersecurity, gen AI, food safety, restaurant chain pricing, quantitative trading analytics, geospatial data, sales pipeline measurement, marketing tech and healthcare.

Pipeline-centric 131

Pipeline-centric Food Healthcare Unstructured Data 131

Striim

JUNE 24, 2025

When data is incomplete or inconsistent, key stakeholders make decisions based on faulty assumptions—forced to rely on outdated reports or fragmented insights. In healthcare, disconnected patient records delay treatment, compromise care coordination, and lead to duplicate testing.

Retail 52

Retail Data Lake Government Healthcare 52

AltexSoft

OCTOBER 25, 2021

Its deep learning natural language processing algorithm is best in class for alleviating clinical documentation burnout, which is one of the main problems of healthcare technology. Microsoft’s move tells a lot about the company’s (and the healthcare industry’s) priorities. Healthcare organizations generate a lot of text data.

Medical 52

Medical Healthcare Process Hospitality 52

ProjectPro

JUNE 6, 2025

Data integration projects revolve around managing this process. They involve combining data from various systems and transforming it into an ideal format for analysis and decision-making. Think of the data integration process as building a giant library where all your data's scattered notebooks are organized into chapters.

Data Integration 40

Data Integration Project Data Lake Hospitality 40

ProjectPro

JUNE 6, 2025

Machine learning is revolutionizing how different industries function, from healthcare to finance to transportation. Data Scientists use machine learning algorithms to predict equipment failures in manufacturing, improve cancer diagnoses in healthcare , and even detect fraudulent activity in 5.

Machine Learning 75

Machine Learning Algorithm Amazon Web Services Healthcare 75

ProjectPro

JUNE 6, 2025

This technology is not confined to one industry but is used across diverse sectors such as healthcare, finance, entertainment, manufacturing, and more. Additionally, companies like PathAI utilize generative AI to improve disease diagnosis by generating high-quality medical images and data analysis in the healthcare sector.

Insurance 52

Insurance Manufacturing Medical Banking 52

Snowflake

NOVEMBER 29, 2023

Technological drivers Data storage: Snowflake provides unprecedented flexibility to store a variety of data sources of all modalities (streaming, structured, semi-structured and unstructured) at a low cost, including omics data such as variant (VCF) data and unstructured data such as pathology images.

Metadata 109

Metadata Healthcare Medical Data Storage 109

phData: Data Engineering

NOVEMBER 8, 2024

It enables analysts and data engineers to “go back in time” and investigate how data looked at specific points, a critical feature for industries with stringent audit requirements, such as finance, healthcare, and e-commerce. They also support ACID transactions, ensuring data integrity and stored data reliability.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

ProjectPro

JUNE 6, 2025

FAQs on Predictive Modelling Techniques Predictive Modeling Techniques - A Gentle Introduction Predictive modeling techniques use existing data to build (or train) a model that can predict outcomes for new data. Predictive modeling also enables the healthcare industry to improve financial management to optimize patient outcomes.

Data Mining 45

Data Mining Banking Retail Healthcare 45

ProjectPro

JUNE 6, 2025

Let us compare traditional data warehousing and Hadoop-based BI solutions to better understand how using BI on Hadoop proves more effective than traditional data warehousing- Point Of Comparison Traditional Data Warehousing BI On Hadoop Solutions Data Storage Structured data in relational databases.

Hadoop 40

Hadoop BI Big Data Business Intelligence 40

ProjectPro

JUNE 6, 2025

Synthetic data, unlike real data, is artificially generated and designed to mimic the properties of real-world data. This blog explores synthetic data generation, highlighting its importance for overcoming data scarcity. MDClone MDClone is a specialized synthetic data generation tool for the healthcare industry.

Healthcare 40

Healthcare Medical Datasets Machine Learning 40

ProjectPro

JUNE 6, 2025

Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., and Flume in Hadoop is used to sources data which is stored in various sources like and deals mostly with unstructured data. The complexity of the big data system increases with each data source.

ETL Tools 40

ETL Tools Hadoop Relational Database Unstructured Data 40

ProjectPro

JUNE 6, 2025

Data Engineering Projects for Practice GCP Data Ingestion with SQL Log Analytics Project Data Engineering Project on COVID-19 Data ETL Developer vs. Data Scientist A data scientist gathers and analyzes vast volumes of structured and unstructured data. Do they build an ETL data pipeline?

Data Engineer 59

Data Engineer Data Engineering Engineering ETL Tools 59

ProjectPro

JUNE 6, 2025

Patient's Sickness Prediction System Machine learning has been proven effective in the field of healthcare also. Traditional healthcare systems became increasingly challenging to cater to the needs of millions of patients. Every modern healthcare equipment and gadget comes with internal apps that can store patient's data.

Machine Learning 69

Machine Learning Project Datasets Algorithm 69

Teradata

JUNE 30, 2025

Unlike traditional data systems designed primarily for historical reporting, AI data architecture must support: Real-time and batch data processing Structured, semi-structured, and unstructured data Automated machine learning pipelines Enterprise-grade governance and security A critical evolution within this framework is the AI factory architecture (..)

Data Architecture 52

Data Architecture Architecture Building Government 52

Snowflake

JUNE 13, 2024

Bringing in batch and streaming data efficiently and cost-effectively Ingest and transform batch or streaming data in <10 seconds: Use COPY for batch ingestion, Snowpipe to auto-ingest files, or bring in row-set data with single-digit latency using Snowpipe Streaming.

Data Ingestion 113

Data Ingestion MySQL PostgreSQL Data Pipeline 113

ProjectPro

JUNE 6, 2025

Benefits of AI in Data Analytics Having understood the challenges with traditional analytics, it's time to understand the real, tangible benefits of using AI in data analytics—from faster decision-making to more inclusive access to valuable insights across teams.

Data Analytics 40

Data Analytics Unstructured Data Datasets BI 40

ProjectPro

JUNE 6, 2025

2015 will witness various phases of big data changing lives to make world a better place by helping businesses make big decisions and solve real world problems. These systems can be related to human brains as they link bits of data to find real answers and not merely search results.

Big Data 40

Big Data Retail Banking Pharmaceutical 40

ProjectPro

JUNE 6, 2025

Maintain data security and set guidelines to ensure data accuracy and system safety. Stay updated with the latest cutting-edge data architecture strategies. Organize and categorize data from various structured and unstructured data sources. Understanding of Data modeling tools (e.g.,

Data Architect 40

Data Architect Data Mining Programming Language Java 40

ProjectPro

JUNE 6, 2025

Larger organizations and those in industries heavily reliant on data, such as finance, healthcare, and e-commerce, often pay higher salaries to attract top Big Data talent. Developers who can work with structured and unstructured data and use machine learning and data visualization tools are highly sought after.

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

JUNE 6, 2025

Automated tools are developed as part of the Big Data technology to handle the massive volumes of varied data sets. Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. IT, Retail, Sales & Marketing, Healthcare, Manufacturing, Education, etc.,

Big Data 40

Big Data Data Engineer Data Engineering Engineering 40

ProjectPro

JUNE 6, 2025

Several companies, from small start-ups to large enterprises, use AWS Athena to solve some of the most brilliant use cases like Anti-money laundering, Security incident responses, Healthcare and patient analytics, customer analytics, and the list goes on. It is a serverless big data analysis tool. What is AWS Athena?,

AWS 67

AWS Big Data SQL Raw Data 67

Snowflake

JANUARY 26, 2023

Advanced analytics shine For a lens into the healthcare sector, we turned to Jesse Cugliotta , Global Industry GTM Lead – Healthcare & Life Sciences at Snowflake: “Advanced analytics that can handle unstructured data will play a bigger role in healthcare data strategies,” says Jesse.

Retail 82

Retail Healthcare Unstructured Data Media 82

ProjectPro

JUNE 6, 2025

Here is a post by Lekhana Reddy , an AI Transformation Specialist, to support the relevance of AI in Data Analytics. As AI expands its applications across diverse sectors—from healthcare to finance—it’s safe to assume that AI will soon be a core skill for professionals across industries.

Data Analytics 40

Data Analytics Healthcare Machine Learning Datasets 40