CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architect vs. data engineer The data architect and data engineer roles are closely related.

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Data Architecture Data Warehouse Statistics Visualization 132

CIO Business Intelligence

JULY 26, 2023

The only thing we have on premise, I believe, is a data server with a bunch of unstructured data on it for our legal team,” says Grady Ligon, who was named Re/Max’s first CIO in October 2022. As for Keller Williams, Chief Technology and Digital Officer Chris Cox sees the cloud as an engine for innovation. “We

Data Lake 98

Data Lake Digital Transformation Machine Learning Data Architecture 98

CIO Business Intelligence

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. When data is stored in a modern, accessible repository, organizations gain newfound capabilities. Connect/Activate.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

IBM Big Data Hub

MAY 19, 2023

Finally, TDC Digital realized it needed to find the right technology partner to offer them a transparent billing system and an appropriate cloud storage solution to help them deliver a differentiated customer experience and drive business growth.

Unstructured Data 81

Unstructured Data Data Processing Manufacturing Data Lake 81

David Menninger's Analyst Perspectives

MARCH 30, 2020

I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data. Here are some of the trends I see continuing to impact data architectures.

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Data Architecture Unstructured Data Data Lake Data Governance 244

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

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.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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Data Quality Data Architecture Strategy Data Lake 52

Jet Global

OCTOBER 30, 2020

Introducing Data Lakes. Microsoft’s next option is called Azure Data Lake Services (ADLS), and it seems to be the company’s favored long-term solution to its D365 F&SCM reporting challenge. Data lake” is a generic term that refers to a fairly new development in the world of big data analytics.

Data Lake 52

Data Lake Unstructured Data Reporting Finance 52

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Text, images, audio, and videos are common examples of unstructured data.

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Unstructured Data Metadata Management Analytics 117

IBM Big Data Hub

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

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Data Warehouse Cost-Benefit Unstructured Data Data Architecture 57

Sisense

OCTOBER 6, 2020

Traditional methods of gathering and organizing data can’t organize, filter, and analyze this kind of data effectively. Advanced technology and new approaches are needed. Qualitative data benefits: Unlocking understanding. Making sense of and deriving patterns from it calls for newer, more advanced technology.

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Statistics Unstructured Data Data-driven Visualization 98

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. This is especially helpful when handling massive amounts of big data.

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Metadata Data Quality Data-driven Data Governance 52

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 111

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Big Data Ecosystem.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 86

Data Lake Analytics Snapshot Optimization 86

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. Meet the data lakehouse.

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Data Lake Unstructured Data Data Warehouse Data Quality 119

CIO Business Intelligence

JUNE 29, 2022

Data Factory includes features such as “ code by example ” to help users build queries but also has options to use languages such as Python, Java, and.NET with Git and CI/CD support, making it particularly useful for migrating SQL Server Integration Services to Azure. Azure Data Explorer. Azure Data Lake Analytics.

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Data Lake Analytics Data Warehouse Machine Learning 116

CIO Business Intelligence

AUGUST 18, 2022

To find out, he queried Walgreens’ data lakehouse, implemented with Databricks technology on Microsoft Azure. “We For Guadagno, the need to match vaccine availability with patient demand came at the right moment, technologically speaking. Lakehouses redeem the failures of some data lakes. That’s how we got here.

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Data Lake Data Warehouse Unstructured Data Business Intelligence 140

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

APRIL 19, 2023

Building an optimal data system As data grows at an extraordinary rate, data proliferation across your data stores, data warehouse, and data lakes can become a challenge. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

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Data Warehouse Data Lake Unstructured Data Optimization 55

BizAcuity

MAY 10, 2022

Cloud technology and innovation drives data-driven decision making culture in any organization. It is the epitome of modern technology right now with multi-dimensional innovations shaping every layer. Cloud technology has been around since the mid-2000s. Cloud technology is a fascinating subject.

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Data-driven IoT Unstructured Data Data Lake 52

CIO Business Intelligence

MAY 24, 2022

Data has always been fundamental to business, but as organisations continue to move to Cloud based environments coupled with advances in technology like streaming and real-time analytics, building a data driven business is one of the keys to success. There are many attributes a data-driven organisation possesses.

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Data-driven Data Lake Data Warehouse Cost-Benefit 98

Sisense

MAY 28, 2019

Operating “in-data” to enable the direct query of unstructured data lakes, providing a visualization layer on top of them. This is typically done on top of a high-performance database and, these days, on top of a cloud data warehouse. To see a BI vendor doubling down on in-data technology isn’t surprising.

Data Analytics 89

Data Analytics Data Lake Analytics Unstructured Data 89

Cloudera

NOVEMBER 18, 2021

Every one of our 22 finalists is utilizing cloud technology to push next-generation data solutions to benefit the everyday people who need it most – across industries including science, health, financial services and telecommunications. The Cloudera technology has also enabled Bank of the West to experiment and scale faster.

Data Lake 73

Data Lake Cost-Benefit Digital Transformation Risk 73

Cloudera

AUGUST 21, 2020

And next to those legacy ERP, HCM, SCM and CRM systems, that mysterious elephant in the room – that “Big Data” platform running in the data center that is driving much of the company’s analytics and BI – looks like a great potential candidate. . What technologies will change or be available 3 years from now? .

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Cost-Benefit Big Data ROI Risk 71

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? Using Alation, ARC automated the data curation and cataloging process. “So

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Data Analytics Analytics Data-driven Big Data 52

AWS Big Data

FEBRUARY 21, 2023

At the heart of all data warehousing is integration, and this layer contains integrated data from multiple sources built around the enterprise-wide business keys. Although data lakes resemble data vaults, a data vault provides more features of a data warehouse.

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Data Warehouse Data Lake Cost-Benefit Modeling 64

Cloudera

JUNE 4, 2018

That’s the equivalent of 1 petabyte ( ComputerWeekly ) – the amount of unstructured data available within our large pharmaceutical client’s business. Then imagine the insights that are locked in that massive amount of data. Nguyen, Accenture & Mitch Gomulinski, Cloudera.

Unstructured Data 45

Unstructured Data Metadata Big Data Enterprise 45

Cloudera

MAY 16, 2018

This example combines three types of unrelated data: Legal entity data: Two companies with completely unrelated business lines (coffee and waste management) merged together; Unstructured data: Fraudulent promotion campaigns took place through press releases and a fake stock-picking robot.

Data Lake 41

Data Lake Risk Visualization Unstructured Data 41

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021! Dig into AI.

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Modeling Big Data IoT Data Warehouse 84

Alation

AUGUST 4, 2022

It’s been one decade since the “ Big Data Era ” began (and to much acclaim!). Analysts asked, What if we could manage massive volumes and varieties of data? Yet the question remains: How much value have organizations derived from big data? Big Data as an Enabler of Digital Transformation.

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Big Data Digital Transformation Data Lake Data-driven 95

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

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Data Architecture Data Lake Machine Learning Data Governance 65

AWS Big Data

JULY 28, 2023

Amazon Redshift now makes it easier for you to run queries in AWS data lakes by automatically mounting the AWS Glue Data Catalog. You no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

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Data Lake Data Governance Data Warehouse Modeling 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. . CRM platforms).

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Data Processing Data Warehouse Enterprise Visualization 88

Jet Global

NOVEMBER 21, 2023

Continued global digitalization is creating huge quantities of data for modern organizations. To have any hope of generating value from growing data sets, enterprise organizations must turn to the latest technology. In the early days of data warehousing technology, data warehouses were built around a single database.

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Data Lake Data Warehouse Reporting Enterprise 52