Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 94

Data Lake Data Warehouse Machine Learning Cost-Benefit 94

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 79

Data Lake Data Warehouse Machine Learning Cost-Benefit 79

erwin

OCTOBER 8, 2020

And you can’t risk false starts or delayed ROI that reduces the confidence of the business and taint this transformational initiative. By using automated and repeatable capabilities, you can quickly and safely migrate data to the cloud and govern it along the way. Regulatory compliance is also a major driver of data governance (e.g.,

Data Governance 145

Data Governance Metadata Testing Data Lake 145

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.

Data Architecture 124

Data Architecture Data Warehouse Statistics Visualization 124

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

IBM Big Data Hub

JANUARY 5, 2023

Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues. Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data.

Risk 70

Risk Modeling Management Metadata 70

Data Virtualization

MARCH 3, 2021

To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is. The post Data Management Challenges for the Modern Enterprise appeared first on Data Virtualization blog.

Enterprise 75

Enterprise Management Strategy Data Lake 75

CIO Business Intelligence

SEPTEMBER 6, 2022

When Steve Pimblett joined The Very Group in October 2020 as chief data officer, reporting to the conglomerate’s CIO, his task was to help the enterprise uncover value in its rich data heritage. As a result, Pimblett now runs the organization’s data warehouse, analytics, and business intelligence.

IT 77

IT Forecasting Data Lake Enterprise 77

CIO Business Intelligence

APRIL 29, 2022

This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Recommendations for Data and AI Leaders. A great example of this is Novartis. To learn more, visit HPE.

Data Governance 142

Data Governance IT Risk Data Lake 142

AWS Big Data

MARCH 29, 2024

However, to analyze trends over time, aggregate from different dimensions, and share insights across the organization, a purpose-built business intelligence (BI) tool like Amazon QuickSight may be more effective for your business. Grafana provides powerful customizable dashboards to view pipeline health.

Metrics 104

Metrics Visualization Dashboards Interactive 104

CIO Business Intelligence

DECEMBER 4, 2023

When you enrich, structure, and operationalize data on the way in, there is no limit to the efficiencies, value streams, and insights unlocked by readily available powerful cloud platform tools. The ways modern data is used, processed, and analyzed are continuously evolving as machine learning technology becomes better at these tasks.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

Octopai

MAY 30, 2019

If the point of Business Intelligence (BI) data governance is to leverage your datasets to support information transparency and decision-making, then it’s fair to say that the data catalog is key for your BI strategy. At least, as far as data analysis is concerned. Choosing a Data Catalog. Scalability.

Metadata 40

Metadata Data Governance Data Lake IoT 40

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 59

Management Enterprise Strategy Data Lake 59

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. But when it’s dirty, stagnant, or hard to unleash, your business will suffer. Benefits of a Data Lake.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 52

Management Enterprise Strategy Data Lake 52

Alation

JANUARY 26, 2023

However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. What’s worse, just 3% of the data in a business enterprise meets quality standards. There’s also no denying that data management is becoming more important, especially to the public.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). for DG adoption in the enterprise. A brief pictorial history.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

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. It required a different data platform solution. It was Datawarehouse.

Data Lake 52

Data Lake Data Warehouse Data-driven 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

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 99

Data Lake Data Warehouse Management Risk 99

Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Towards Data Science ). Forrester ).

Data Architecture 79

Data Architecture Data Lake Metadata Data Warehouse 79

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.

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Data Warehouse Data Lake Analytics Machine Learning 100

Cloudera

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Supercharge your data lakehouse, make it open.

Data Lake 88

Data Lake Data Architecture Metadata Data Warehouse 88

CIO Business Intelligence

SEPTEMBER 12, 2023

What’s changed since then, apart from Shih’s title, is Salesforce has rearchitected its underlying Data Cloud and Einstein AI framework to use an improved metadata framework, creating a new platform it calls Einstein 1. Einstein 1 As with any AI, data is an essential ingredient for making generative AI work.

IT 106

IT Metadata Data Lake Cost-Benefit 106

AWS Big Data

JUNE 13, 2023

Amazon QuickSight is a scalable, serverless, embeddable, machine learning (ML) powered business intelligence (BI) service built for the cloud that supports identity federation in both Standard and Enterprise editions. Download the SAML metadata file. In the navigation pane under Clients , import the SAML metadata file.

Metadata 52

Metadata Dashboards Business Intelligence Management 52

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. 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.

Data Lake 99

Data Lake Unstructured Data Data Warehouse Data Quality 99

Alation

MARCH 29, 2021

This is why the ability to quickly search and discover data across the enterprise is the first step towards data-driven decision making. In this blog, we will discuss how data catalogs accelerate search & discovery. How metadata accelerates search & discovery. Not all data catalogs are created equal.

Metadata 59

Metadata Data-driven Enterprise Machine Learning 59

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance. Proprietary file formats mean no one else is invited in!

Data Lake 94

Data Lake Data Warehouse IT Analytics 94

IBM Big Data Hub

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. It enables secure data sharing for analytics and AI across your ecosystem.

Cost-Benefit 76

Cost-Benefit Metadata Optimization Management 76

AWS Big Data

NOVEMBER 29, 2023

Knowledge Bases works with popular vector databases and engines including Amazon OpenSearch Serverless , Redis Enterprise Cloud, and Pinecone, with support for Amazon Aurora and MongoDB coming soon. Of course, the value of a strong data foundation is not new and the need for one spans well beyond generative AI.

Data Warehouse 109

Data Warehouse Data Lake Dashboards Data Integration 109

Alation

APRIL 14, 2022

Moving data to the cloud can bring immense operational benefits. However, the sheer volume and complexity of today’s enterprise data can cause downstream headaches for data users. Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. Cloud governance.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

IBM Big Data Hub

OCTOBER 12, 2023

Ensuring compliance with governmental regulatory requirements as well as internal policies An AI model must be fully understood from every angle, inside and out—from what enterprise data is used and when , to how the model arrived at a certain output. Learn more about IBM watsonx 1.

Cost-Benefit 76

Cost-Benefit Metadata Data Governance Modeling 76

AWS Big Data

FEBRUARY 21, 2023

Because data is closer to the source and stored in raw format, it has to be transformed before it can be used for reporting and other application purposes. This is one of the biggest hurdles with the data vault approach. It is a data modeling methodology designed for large-scale data warehouse platforms.

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Metadata 65