erwin

OCTOBER 8, 2020

The desire to modernize technology, over time, leads to acquiring many different systems with various data entry points and transformation rules for data as it moves into and across the organization. The metadata-driven suite automatically finds, models, ingests, catalogs and governs cloud data assets.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

CIO Business Intelligence

AUGUST 2, 2023

A data and analytics capability cannot emerge from an IT or business strategy alone. With both technology and business organization deeply involved in the what, why, and how of data, companies need to create cross-functional data teams to get the most out of it. That strategy is doomed to fail.

Manufacturing 79

Manufacturing Data Architecture Strategy Data Strategy 79

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. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 92

Data Lake Data Warehouse Metadata Data Architecture 92

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. Further, data management activities don’t end once the AI model has been developed. Addressing the Challenge.

Data Governance 141

Data Governance IT Risk Data Lake 141

CIO Business Intelligence

OCTOBER 1, 2022

It requires taking data from equipment sensors, applying advanced analytics to derive descriptive and predictive insights, and automating corrective actions. The end-to-end process requires several steps, including data integration and algorithm development, training, and deployment.

Manufacturing 143

Manufacturing Digital Transformation IoT Internet of Things 143

Jet Global

OCTOBER 7, 2020

For organizations considering a move to Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM), or for those in the early stages of an implementation project, defining a clear strategy for curating data is a key to developing a comprehensive approach to reporting and analytics. What Are Data Entities?

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

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.

Enterprise 76

Enterprise Management Strategy Data Lake 76

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 85

Data Lake Analytics Snapshot Optimization 85

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 IT 59

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 IT 52

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

Domino Data Lab

APRIL 3, 2019

The longer answer is that in the context of machine learning use cases, strong assumptions about data integrity lead to brittle solutions overall. So we had three tiers providing a separation of concerns: presentation, logic, data. Note that data warehouse (DW) and business intelligence (BI) practices both emerged circa 1990.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

CIO Business Intelligence

MAY 24, 2022

Australian research and advisory firm Adapt identifies an organisation’s ability to execute a data-driven strategy as one of 12 core competencies , identified from 30,000 conversations spanning three years with leading IT and businesses. This is the first post in a series of three on data-driven organisations.

Data-driven 77

Data-driven Data Lake Data Warehouse Cost-Benefit 77

CIO Business Intelligence

FEBRUARY 22, 2024

Increasing pressures around environment, social, and governance (ESG) concerns have organizations across industries turning to their CIOs to revamp their strategies for ESG reporting. To date, many companies have merely repurposed existing technology solutions for their ESG reporting needs. “The

Software 75

Software Reporting KPI Enterprise 75

AWS Big Data

JULY 13, 2023

This post discusses the journey that took Altron from their initial goals, to technical implementation, to the business value created from understanding their customers and their unique opportunities better. Foundations for a data lake with data governance controls and data quality checks.

Optimization 88

Optimization B2B Data Quality Sales 88

AWS Big Data

FEBRUARY 21, 2023

Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face. What is a dimensional data model? It optimizes the database for faster data retrieval.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

CIO Business Intelligence

MARCH 22, 2022

To companies entrenched in decades-old business and IT processes, data fiefdoms, and legacy systems, the task may seem insurmountable. Develop a strategy to liberate data . Which type(s) of storage consolidation you use depends on the data you generate and collect. . Just starting out with analytics?

Analytics 93

Analytics Key Performance Indicator Data Warehouse Data-driven 93

CIO Business Intelligence

SEPTEMBER 22, 2023

The term “data management platform” can be confusing because, while it sounds like a generalized product that works with all forms of data as part of generalized data management strategies, the term has been more narrowly defined of late as one targeted to marketing departments’ needs. Of course, marketing also works.

Management 98

Management Advertising Data Lake Sales 98

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

JULY 19, 2023

We show how to perform extract, transform, and load (ELT), an integration process focused on getting the raw data from a data lake into a staging layer to perform the modeling. Data can either be loaded when there is a new sale, or daily; this is where the inserted date or load date comes in handy.

Modeling 67

Modeling Sales Data Warehouse Snapshot 67

Cloudera

MAY 16, 2018

The Keystone to a Holistic Trade Surveillance Strategy. However, in this case, that output is ingested into a data lake. Instead of each group’s tools acting on the output in isolation, they leverage a common visual analytics platform that is native to the lake and uses all of the data without moving it to a separate server.

Data Lake 41

Data Lake Risk Visualization Unstructured Data 41

AWS Big Data

NOVEMBER 13, 2023

As your company transforms, you need a data foundation for business applications, new technical innovations, and data-driven business initiatives. With new capabilities for self-service and simpler builder experiences, you can democratize data access for line-of-business users, analysts, scientists, and engineers.

Analytics 112

Analytics Data Lake Data Warehouse Data-driven 112

AWS Big Data

NOVEMBER 29, 2023

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. The team uses dbt-glue to build a transformed gold model optimized for business intelligence (BI).

Data Lake 102

Data Lake Management Metrics Data Warehouse 102

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. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52