AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data warehouse is one of the components in a data hub.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

Octopai

SEPTEMBER 10, 2020

Business Intelligence & Analytics: It’s a hard knock life for these guys. That’s often code for “working nights and weekends tracking down bugs and data errors, taking the blame if the data doesn’t give the ‘right’ answer, and being held accountable when unrealistic timelines aren’t met.”.

Business Intelligence 52

Business Intelligence Data Warehouse Dashboards Reporting 52

CIO Business Intelligence

MAY 24, 2022

Some of the accelerators included as part of the new platform are integrations with Salesforce, NPI data, National Patient Account Services, Workday, Oracle Fusion HCM Cloud, Orange HRM, Salesforce Health Cloud, MedPro, healthcare-focused cloud company Veeva, and HR vendor UltiPro. Analytics for faster decision making.

Finance 127

Finance Management Metadata Data Quality 127

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 124

Data Architecture Data Warehouse Statistics Visualization 124

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

JUNE 26, 2020

Given the value this sort of data-driven insight can provide, the reason organizations need a data catalog should become clearer. It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., Three Types of Metadata in a Data Catalog. Technical Metadata.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If not, before adopting a cloud data warehouse, consider the true costs of a cloud-native data warehouse. These costs impede the adoption of cloud-native data warehouses.

Data Warehouse 98

Data Warehouse Metadata Cost-Benefit Optimization 98

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

AWS Big Data

NOVEMBER 29, 2023

The Eightfold Talent Intelligence Platform powered by Amazon Redshift and Amazon QuickSight provides a full-fledged analytics platform for Eightfold’s customers. It delivers analytics and enhanced insights about the customer’s Talent Acquisition, Talent Management pipelines, and much more.

Metadata 102

Metadata Data Warehouse Analytics Data Analytics 102

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Creating a data architecture roadmap.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads.

Management 94

Management Data Warehouse Metrics Dashboards 94

Octopai

OCTOBER 20, 2021

Octopai, the leader in automated data lineage, data catalog and data discovery, announced today its support and analysis of Amazon Redshift, one of the fastest and most widely used cloud data warehouses.

Metadata 52

Metadata Data Warehouse Enterprise Business Intelligence 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. How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools.

Risk 70

Risk Modeling Management Metadata 70

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. They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing.

Data Lake 102

Data Lake Sales Data Warehouse Snapshot 102

TDAN

MARCH 19, 2019

Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years. The emergence of various new concepts, technologies, and applications such as Hadoop, Tableau, R, Power BI, or Data Lakes indicate that changes are under way.

Management 84

Management Data Lake Data Warehouse Analytics 84

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. Meaningful business context. Improved trust and confidence in data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

CIO Business Intelligence

NOVEMBER 22, 2022

“Unique insights derived from an organization’s data constitute a competitive advantage that’s inherent to their business and not easily copied by competitors,” she observes. Failing to meet these needs means getting left behind and missing out on the many opportunities made possible by advances in data analytics.”

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

datapine

SEPTEMBER 29, 2022

6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes. Industry-wide, the positive ROI on quality data is well understood. 2 – Data profiling. 4 – Data Reporting.

Data Quality 241

Data Quality Metrics Data-driven Management 241

datapine

MAY 29, 2019

BI architecture has emerged to meet those requirements, with data warehousing as the backbone of these processes. One of the BI architecture components is data warehousing. What Is Data Warehousing And Business Intelligence? BI Architecture Framework In Modern Business. Data integration. Data storage.

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

Octopai

JUNE 15, 2020

Business intelligence databases are dynamic repositories that must often be adjusted based on organizational and or regulatory requirements. Faced with these data limitations, the insurance company reached out to Octopai. With the implementation of these data lineage tools, the process was streamlined.

Insurance 52

Insurance Metadata Business Intelligence Data Warehouse 52

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. The sample dashboard showed metrics over time, top errors, and comparative job analytics.

Metrics 104

Metrics Visualization Dashboards Interactive 104

Sisense

FEBRUARY 17, 2020

Before getting started, you’ll need to grant access to the SNOWFLAKE metadata schema where the ACCOUNT_USAGE tables are. Monitor trends in query performance to optimize user experience, including ad hoc analytics and business intelligence created on Snowflake. Step 0: Granting access to the tables.

Dashboards 80

Dashboards Data Warehouse Metadata Business Intelligence 80

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Octopai

JUNE 1, 2020

Let’s look at how these new requirements have changed the data landscape and how automated data mapping can give your company an advantage. Value of Data Mapping. If your company is merging with another or combining departments, data mapping allows for accurate data integration.

Metadata 52

Metadata Data Warehouse Data Integration Finance 52

CIO Business Intelligence

SEPTEMBER 6, 2022

Behind the flagship brand, though, he says data remained scattered in siloes across many legacy business units and applications, with limited automation, many glossaries, and complex data lineage, and stewardship making it hard to govern and audit. Establishing a clear and unified approach to data.

IT 77

IT Forecasting Data Lake Enterprise 77

erwin

APRIL 27, 2022

In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis. Change Data Capture identifies and processes only the data that has changed and stores the changed data in a form so as to be of further use.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

FineReport

NOVEMBER 17, 2021

It was an American interactive data visualization software company of business intelligence. Data Management. Tableau : There are specialized modules to manage metadata. FineReport: When organizing data management, we may face data source replacement. Meanwhile, Domo grows external data value.

KPI 52

KPI Dashboards Metadata Data Warehouse 52

Alation

DECEMBER 21, 2022

Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management. Early on, analysts used data catalogs to find and understand data more quickly. The MDM tool should help with this.

Management 52

Management Data Quality Metadata Testing 52

Peter James Thomas

AUGUST 18, 2018

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

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

SEPTEMBER 7, 2021

With Snowflake, data stewards have a choice to leverage Snowflake’s governance policies. First, stewards are dependent on data warehouse admins to provide information and to create and edit enforcement policies in Snowflake. Data quality details signal to users whether data can be trusted or used.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

AWS Big Data

MAY 7, 2024

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. The producer also needs to manage and publish the data asset so it’s discoverable throughout the organization.

Metadata 74

Metadata Data Lake Data Processing Data-driven 74

CIO Business Intelligence

MARCH 8, 2023

SAP’s Data Warehouse Cloud is evolving, gaining new features and a new name, Datasphere, as the company addresses continued diversification of the enterprise data. Khan said SAP is going beyond the usual capabilities of a data fabric by preserving the business context of the data it carries. “But

Data Warehouse 52

Data Warehouse Metadata Enterprise Machine Learning 52

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Iceberg stores the metadata pointer for all the metadata files.

Data Lake 92

Data Lake Data Warehouse Metadata Data Architecture 92