AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

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Data Lake Sales Data Warehouse Snapshot 99

AWS Big Data

MARCH 25, 2024

This data store provides your organization with the holistic customer records view that is needed for operational efficiency of RAG-based generative AI applications. For building such a data store, an unstructured data store would be best. This is typically unstructured data and is updated in a non-incremental fashion.

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Data Lake Unstructured Data Management Modeling 87

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. Nasdaq’s massive data growth meant they needed to evolve their data architecture to keep up.

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Data Warehouse Data Lake Unstructured Data Optimization 56

AWS Big Data

JANUARY 8, 2024

Kinesis Data Streams has native integrations with other AWS services such as AWS Glue and Amazon EventBridge to build real-time streaming applications on AWS. Refer to Amazon Kinesis Data Streams integrations for additional details. It provides the ability to collect data from tens of thousands of data sources and ingest in real time.

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Analytics IoT Data-driven Snapshot 109

CIO Business Intelligence

APRIL 4, 2023

Businesses that lead in fully deploying AI will be able to optimize customer experiences and efficiencies that help maximize customer retention and customer acquisition and gain a distinct advantage over the competition. In order to move AI forward, we need to first build and fortify the foundational layer: data architecture.

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Data Architecture Data Lake Data Warehouse Cost-Benefit 52

CIO Business Intelligence

NOVEMBER 25, 2022

Today, more than 90% of its applications run in the cloud, with most of its data is housed and analyzed in a homegrown enterprise data warehouse. Like many CIOs, Carhartt’s top digital leader is aware that data is the key to making advanced technologies work. Today, we backflush our data lake through our data warehouse.

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Data Lake Data Warehouse Unstructured Data Data Architecture 128

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. Pulling it all together.

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Data Lake Unstructured Data Data Warehouse Data Quality 119

BizAcuity

APRIL 14, 2022

There are a wide range of problems that are presented to organizations when working with big data. Challenges associated with Data Management and Optimizing Big Data. Unscalable data architecture. Scalable data architecture is not restricted to high storage space. Unstructured Data Management.

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Big Data Data Analytics Management Unstructured Data 52

Cloudera

SEPTEMBER 12, 2022

And second, for the data that is used, 80% is semi- or unstructured. Combining and analyzing both structured and unstructured data is a whole new challenge to come to grips with, let alone doing so across different infrastructures. Cloudera has supported data lakehouses for over five years. Better together.

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Unstructured Data Data Architecture Data Lake Snapshot 75

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

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Data Lake Metadata Optimization Statistics 110

IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. MLOps creates a process where it’s easier to cull insights from business data.

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Data Architecture Data Lake Machine Learning Data Governance 65

Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. What Is the Role of the Cloud in Data Modernization?

Cost-Benefit 52

Cost-Benefit Data Governance Manufacturing Data Architecture 52