AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Precisely

FEBRUARY 9, 2024

In 2023, organizations dealt with more data than ever and witnessed a surge in demand for artificial intelligence use cases – particularly driven by generative AI. They relied on their data as a critical factor to guide their businesses to agility and success.

Data Integration 69

Data Integration Government Data Metadata 69

Snowflake

APRIL 13, 2025

Many enterprises face overwhelming data sources, from structured databases to unstructured social media feeds. Agentic AI automates these processes, helping ensure data integrity and offering real-time insights. A path forward Agentic AI represents a change in thinking in enterprise data management.

Data Management 70

Data Management Management Consulting Unstructured Data 70

Striim

AUGUST 31, 2023

Showing how Kappa unifies batch and streaming pipelines The development of Kappa architecture has revolutionized data processing by allowing users to quickly and cost-effectively reduce data integration costs. Stream processors, storage layers, message brokers, and databases make up the basic components of this architecture.

Data Integration 69

Data Integration Architecture Amazon Web Services Machine Learning 69

Striim

APRIL 18, 2025

Eliminating Data Silos with Unified Integration Rather than storing data in isolated systems, organizations are adopting real-time data integration strategies to unify structured and unstructured data across databases, applications, and cloud environments. Heres how they are tackling these issues: 1.

High Quality Data 52

High Quality Data Business Intelligence Unstructured Data Data Pipeline 52

Precisely

MAY 13, 2024

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. The right data integration solution helps you streamline operations, enhance data quality, reduce costs, and make better data-driven decisions.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Data Engineering Weekly

JULY 14, 2024

link] Sponsored: 7/25 Amazon Bedrock Data Integration Tech Talk Streamline & scale data integration to and from Amazon Bedrock for generative AI applications. Senior Solutions Architect at AWS) Learn about: Efficient methods to feed unstructured data into Amazon Bedrock without intermediary services like S3.

Data Engineering 98

Data Engineering Data Engineer Engineering Unstructured Data 98

phData: Data Engineering

NOVEMBER 8, 2024

A data lakehouse integrates the best features of a data lake and a data warehouse, creating a hybrid architecture that can manage structured and unstructured data using open data formats and allows users to access data using any tool.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Ascend.io

DECEMBER 14, 2022

As data became the backbone of most businesses, data integration emerged as one of the most significant challenges. Today, a good part of the job of a data engineer is to move data from one place to another by creating pipelines that can be either ETL vs. ELT. However, that is less and less the case.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 52

Snowflake

SEPTEMBER 7, 2023

By leveraging External Access with Snowpark, Omnata have launched the first fully native data integration product built on Snowflake which supports syncing data both to and from external Software-As-a-Service applications. Now users with USAGE privilege on the CHATGPT function can call this UDF.

Amazon Web Services 134

Amazon Web Services AWS Government Python 134

Snowflake

JULY 1, 2024

Text and sentiment analysis Gen AI capabilities can help analyze unstructured data from claim notes, customer emails and call transcripts to glean insights into claim complexity, customer sentiment and potential dissatisfaction or fraud. Insurers can use this information to tighten their processes and reduce overall claims costs.

Insurance 112

Insurance Media Machine Learning Unstructured Data 112

Snowflake

JUNE 4, 2024

Generative AI presents enterprises with the opportunity to extract insights at scale from unstructured data sources, like documents, customer reviews and images. It also presents an opportunity to reimagine every customer and employee interaction with data to be done via conversational applications.

Data Security 121

Data Security Machine Learning Unstructured Data SQL 121

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

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

phData: Data Engineering

NOVEMBER 1, 2024

Strong data governance also lays the foundation for better model performance, cost efficiency, and improved data quality, which directly contributes to regulatory compliance and more secure AI systems. To ensure data quality, platforms need consistent, automated processes with continuous testing and validation.

Government 52

Government Data Governance Finance Metadata 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 98

Data Engineering Data Engineer Engineering Data Lake 98

Cloudera

FEBRUARY 15, 2024

Improved data accessibility: By providing self-service data access and analytics, modern data architecture empowers business users and data analysts to analyze and visualize data, enabling faster decision-making and response to regulatory requirements.

Insurance 88

Insurance Banking Data Architecture Data Ingestion 88

Precisely

MARCH 7, 2024

AI technology can ingest and synthesize large volumes of both structured and unstructured data very quickly, offering claims guidance that helps adjusters to better assess cases. eBook Achieving Data Integrity: A Guide for Insurers Technology-driven insights and capabilities depend on trusted data.

Insurance 72

Insurance Process Medical Data Governance 72

Precisely

SEPTEMBER 6, 2023

However, fewer than half of survey respondents rate their trust in data as “high” or “very high.” ” Poor data quality impedes the success of data programs, hampers data integration efforts, limits data integrity causing big data governance challenges.

Data Governance 52

Data Governance Big Data Government Unstructured Data 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 114

Metadata Healthcare Medical Data Storage 114

Precisely

MARCH 9, 2023

We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data. Precisely helps enterprises manage the integrity of their data.

Data Lake 59

Data Lake Data Warehouse Hadoop Raw Data 59

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines.

Consulting 121

Consulting Machine Learning Data Science Data Pipeline 121

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 114

Data Ingestion MySQL PostgreSQL Data Pipeline 114

Data Engineering Weekly

APRIL 7, 2024

[link] Matt Turck: Full Steam Ahead: The 2024 MAD (Machine Learning, AI & Data) Landscape Coninue the week of insights into the world of data & AI landscape, the 2024 MAD landscape is out. It is evident that it will become the foundation of trusted sources, which is essential to taking advantage of advancements from LLMs.

Data Engineering 71

Data Engineering Data Engineer Engineering Unstructured Data 71

Knowledge Hut

APRIL 23, 2024

They also facilitate historical analysis, as they store long-term data records that can be used for trend analysis, forecasting, and decision-making. Big Data In contrast, big data encompasses the vast amounts of both structured and unstructured data that organizations generate on a daily basis.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Striim

MARCH 4, 2025

Automated Categorization: Instantly classifies financial, healthcare, and personal identity information, delivering real-time insights into data security. Quality Oversight: Monitors data integrity continuously, alerting teams when sensitive data appears where it shouldnt.

Data Governance 40

Data Governance Government Healthcare NoSQL 40

Monte Carlo

OCTOBER 10, 2024

Let’s dive into the responsibilities, skills, challenges, and potential career paths for an AI Data Quality Analyst today. Table of Contents What Does an AI Data Quality Analyst Do? Handling unstructured data Many AI models are fed large amounts of unstructured data, making data quality management complex.

Unstructured Data 52

Unstructured Data Google Cloud Machine Learning ETL Tools 52

AltexSoft

SEPTEMBER 23, 2021

A data hub is a central mediation point between various data sources and data consumers. It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. An ETL approach in the DW is considered slow, as it ships data in portions (batches.)

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Data integration , on the other hand, happens later in the data management flow.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. Introduction.

Architecture 124

Architecture Metadata Kafka Government 124

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 66

Data Cleanse Data Governance Unstructured Data Cloud Storage 66

Cloudera

NOVEMBER 22, 2021

Open source frameworks such as Apache Impala, Apache Hive and Apache Spark offer a highly scalable programming model that is capable of processing massive volumes of structured and unstructured data by means of parallel execution on a large number of commodity computing nodes. .

Hadoop 94

Hadoop Government Data Security Cloud 94

ProjectPro

SEPTEMBER 30, 2014

While the initial era of ETL ignited enough sparks and got everyone to sit up, take notice and applaud its capabilities, its usability in the era of Big Data is increasingly coming under the scanner as the CIOs start taking note of its limitations. Industry experts place a great emphasis on individuals to learn Hadoop.

Hadoop 52

Hadoop ETL Tools Unstructured Data ETL System 52

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

DareData

JANUARY 30, 2023

AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS). Talend Data Fabric: A comprehensive data management platform that includes a range of tools for data integration, data quality, and data governance. Examples of NoSQL databases include MongoDB or Cassandra.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Wayne Yaddow

MARCH 14, 2025

Instead of relying on one-off scripts or unstructured transformation logic, dbt Core structures transformations as models, linking them through a Directed Acyclic Graph (DAG) that automatically handles dependencies. The following categories of transformations pose significant limitations for dbt Cloud and dbtCore : 1.

Unstructured Data 52

Unstructured Data SQL Data Pipeline Data Validation 52