CIO Business Intelligence

JUNE 23, 2022

We deliver cloud-native data analytics across the full data lifecycle – data distribution, data engineering, data warehousing, transactional data, streaming data, data science, and machine learning – that’s portable across infrastructures. Jonathan Takiff / IDG.

IT 73

IT Data Architecture Unstructured Data Big Data 73

AWS Big Data

MARCH 10, 2023

However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes. Additionally, the task of maintaining and managing files in the data lake can be tedious and sometimes complex. The Iceberg table is synced with the AWS Glue Data Catalog.

Data Lake 102

Data Lake Sales Data Warehouse Snapshot 102

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Deploying modern data architectures. Lack of sharing hinders the elimination of fraud, waste, and abuse. Forrester ).

Data Architecture 79

Data Architecture Data Lake Metadata Data Warehouse 79

Peter James Thomas

AUGUST 18, 2018

Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. Of course some architectures featured both paradigms as well. This required additional investments in metadata.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 88

Data Lake Data Architecture Metadata Data Warehouse 88

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 100

Data Warehouse Data Lake Analytics Machine Learning 100

Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. The Cloud Data Migration Challenge. On-premises business intelligence and databases. Cloud governance.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. Data fabric promotes data discoverability. It was Datawarehouse.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

IBM Big Data Hub

JULY 13, 2023

The more complete, accurate and consistent a dataset is, the more informed business intelligence and business processes become. Data science tasks such as machine learning also greatly benefit from good data integrity. The post Data integrity vs. data quality: Is there a difference?

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

TDAN

AUGUST 6, 2019

Deep learning, as defined by MathWorks, is a system of artificial intelligence that is built around learning by example. Multiple industries have already understood the benefits that deep learning brings to their operational capabilities.

Deep Learning 81

Deep Learning Technology Data Architecture Metadata 81

CIO Business Intelligence

MARCH 9, 2022

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. If only there were a best-of-both-worlds compromise. .

Data Lake 99

Data Lake Unstructured Data Data Warehouse Data Quality 99

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. These data pipelines generate valuable insights and curated data that are stored in Apache Iceberg tables for downstream usage.

Data Lake 87

Data Lake Analytics Snapshot Optimization 87

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.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

AWS Big Data

APRIL 28, 2023

The third post will show how end-users can consume data from their tool of choice, without compromising data governance. This will include how to configure Okta, AWS Lake Formation , and a business intelligence tool to enable SAML-based federated use of Athena for an enterprise BI activity.

Data Governance 65

Data Governance Management Data-driven Data Lake 65

AWS Big Data

JUNE 10, 2024

This amalgamation empowers vendors with authority over a diverse range of workloads by virtue of owning the data. This authority extends across realms such as business intelligence, data engineering, and machine learning thus limiting the tools and capabilities that can be used. SparkActions.get().expireSnapshots(iceTable).expireOlderThan(TimeUnit.DAYS.toMillis(7)).execute()

Data Lake 99

Data Lake Metadata Snapshot Analytics 99

Ontotext

AUGUST 4, 2023

A data fabric utilizes an integrated data layer over existing, discoverable, and inferenced metadata assets to support the design, deployment, and utilization of data across enterprises, including hybrid and multi-cloud platforms. It also helps capture and connect data based on business or domains.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

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. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

BI-Survey

FEBRUARY 6, 2020

Today’s data-literate users want governed and scalable self-service BI functions to answer critical business questions and to get the most out of their data assets. Most prominently, machine learning (ML) enables improvements in various fields. Linking data to business metadata is crucial for data governance.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

Jet Global

MAY 1, 2023

Learn how embedded analytics are different from traditional business intelligence and what analytics users expect. Embedded Analytics Definition Embedded analytics are the integration of analytics content and capabilities within applications, such as business process applications (e.g., CRM, ERP, EHR/EMR) or portals (e.g.,

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52