AWS Big Data

MARCH 7, 2023

This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. A data hub contains data at multiple levels of granularity and is often not integrated. Let’s look at the components of the architecture in more detail.

Analytics 96

Analytics Data Warehouse Data Lake Metadata 96

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Why keep data at all?

Metadata 64

Metadata Data Governance Dashboards Software 64

AWS Big Data

JUNE 25, 2024

When you deploy a data stream from Amazon Redshift to Data Cloud, an external data lake object (DLO) is created within the Data Cloud environment. This external DLO acts as a storage container, housing metadata for your federated Redshift data.

Data Lake 122

Data Lake Cost-Benefit Data-driven Data Warehouse 122

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. Then, you transform this data into a concise format. Sandipan Bhaumik (Sandi) is a Senior Analytics Specialist Solutions Architect at AWS.

Data Strategy 98

Data Strategy Strategy Data Warehouse Prescriptive Analytics 98

TDAN

MARCH 16, 2021

No matter where data comes from, becoming data-driven depends on every member of your organization being able to find, access, and use the data they need.

Business Objectives 87

Business Objectives Data-driven IT Metadata 87

IBM Big Data Hub

JUNE 30, 2022

The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with business objectives. This requires a deep understanding of the organization’s strengths and weaknesses.

Data Strategy 56

Data Strategy Strategy Business Objectives Data-driven 56

AWS Big Data

AUGUST 5, 2024

For example, a marketing analysis data product can bundle various data assets such as marketing campaign data, pipeline data, and customer data. With the grouping capabilities of data products, data producers can manage and control access to the underlying data assets with just a few steps.

Metadata 59

Metadata Sales Data Lake Publishing 59

IBM Big Data Hub

JANUARY 5, 2023

Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads. Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

Alation

MARCH 14, 2023

It should make data available, maintain data consistency and accuracy, and support data security. Gartner describes it as ‘ a highly dynamic process employed to support the acquisition, organisation, analysis, and delivery of data in support of business objectives ’. Why is a data strategy important?

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

Alation

FEBRUARY 10, 2022

Let’s discuss what data classification is, the processes for classifying data, data types, and the steps to follow for data classification: What is Data Classification? Either completed manually or using automation, the data classification process is based on the data’s context, content, and user discretion.

Data Governance 52

Data Governance Risk Insurance Business Objectives 52

Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. It embraces the reality of business and specialized data needs within teams and organizations.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

Ontotext

MAY 16, 2024

The opportunities exist when you gain the trust across stakeholders that there is a path to ensure that data is true to original intent, defined at a granular level and in a format that is traceable, testable, and flexible to use. Knowledge Graph Development The Graph CoE should lead the development of each of the knowledge graph components.

Enterprise 52

Enterprise Data-driven Cost-Benefit Business Objectives 52

O'Reilly on Data

JULY 28, 2020

Internally, AI PMs must engage stakeholders to ensure alignment with the most important decision-makers and top-line business metrics. Put simply, no AI product will be successful if it never launches, and no AI product will launch unless the project is sponsored, funded, and connected to important business objectives.

Marketing 364

Marketing Experimentation Metrics Testing 364

AWS Big Data

MARCH 13, 2025

Open source Pinot requires in-house expertise that can challenge well-established technical teams to provision hardware, configure environments, tune performance, maintain security, adhere to data governance requirements, manage software updates, and constantly monitor for system issues.

Management 105

Management Analytics OLAP Online Analytical Processing 105

AWS Big Data

OCTOBER 24, 2024

This will import the metadata of the datasets and run default data discovery. Tag the data fields Immuta automatically tags the data members using a default framework. Industry use cases The following are example industry use cases where Immuta and Amazon Redshift integration adds value to customer business objectives.

Data Warehouse 111

Data Warehouse Business Objectives Data-driven Management 111

Ontotext

AUGUST 21, 2024

The opportunities exist when you gain the trust across stakeholders that there is a path to ensure that data is true to original intent, defined at a granular level and in a format that is traceable, testable, and flexible to use.

Knowledge Discovery 52

Knowledge Discovery Cost-Benefit Data-driven Metadata 52