Analyst Reports

Use your Gartner login to see what the Analysts are saying about CluedIn.

quality-1

Building Automation Into Your Data Quality Initiatives

Data Quality

With the growing volume and complexity of datasets entering organizations, automation is required to scale data quality practices. Data and analytics technical professionals should use this research to learn how AI and metadata will support the automation of data quality processes.
 

integration4

Assessing Cloud Data Integration Options

Data Integration

The proliferation of data across on-premises and cloud environments has prompted organizations to fortify their cloud data integration strategy. Data and analytics technical professionals need to craft an adaptable CDI architecture that optimizes integration of heterogeneous and multifaceted data.
 
data-management-1

2021 Planning Guide for Data Management

Data Management

Data and analytics technical professionals are struggling to understand, prioritize and apply innovations to deliver business results. This document introduces the technology, platform and process trends in data management for 2021, and guides organizations toward the right technical decision.

4.quality

Demystifying the Data Fabric

Data Fabric

In a world where global events can suddenly affect the need for new data, data management agility becomes mission-critical. Data and analytics technical professionals can use this research to determine whether a data fabric can be used to provide such agility in their organization.

 

4.quality

Data Quality Fundamentals for Data and Analytics Technical Professionals

Data Quality

As the volume and variety of data continue to grow, data and analytics technical professionals continue to struggle with delivering quality data to consumers. Use this research to understand what quality means and how data management tools work together to achieve high-quality data.
 
2.unify-data

Solution Comparison for 7 Data Fabric Offerings

Data Quality

Data fabric is quickly becoming the next major data management and data integration pattern to consider. This document establishes a framework to be used by data and analytics technical professionals when evaluating data fabric offerings and evaluates seven representative offerings.

07.Connections-filtered

Market Guide for Active Metadata Management

Data Quality

The increased demand for orchestrating existing and new systems has rendered traditional metadata practices insufficient. Organizations are demanding “active metadata” to assure augmented data management capabilities.


Gartner-cool-vendor

Cool Vendors in Data Management

Data Quality

Augmented capabilities are becoming the major differentiators for today’s data management solutions. These Cool Vendors offer data and analytics leaders ways to connect, ingest, analyze and share data more quickly and at a lower cost.


Asset 124

How to Activate Metadata to Enable a Composable Data Fabric

KYC - Know Your Customer

Existing data management solutions contain an abundance of metadata that most organizations find difficult to identify, much less analyze. Data and analytics leaders can reuse existing metadata to build the data fabric for the enterprise and simultaneously get real value from enterprise metadata.

4.master

How to Monetize Data Assets With Your Data and Analytics Service Provider

Data Fabrics

Data monetization is a significant opportunity for digital business success, yet data and analytics leaders struggle to create value from their data assets. Partnering to develop a co-creation model with data and analytics service providers can accelerate the initiatives for business value creation.
 

1.data-lakes

Smart Data Sharing Requires Mapping Use Cases to Architectures and Vendor Solutions

Data Foundation

Without data sharing, organizations will not maximize the value of their data and analytics strategies. Data and analytics leaders should be deliberate in their choice of data sharing architectures, and ensure that the selected vendor offerings serve the desired business purpose.
 
2.compliance

Modern Data and Analytics Requirements Demand a Convergence of Data Management Capabilities

Let's talk data

Data fabric is an important emerging trend that requires a combination of multiple established and emerging data and analytics technologies. Product leaders must ultimately offer complete data fabric solutions via a combination of their own products and strategic partnerships.

1.myd

Emerging Technologies: Data Fabric Is the Future of Data Management

Let's talk data

Data fabric is an important emerging trend that requires a combination of multiple established and emerging data and analytics technologies. Product leaders must ultimately offer complete data fabric solutions via a combination of their own products and strategic partnerships.
 

1.1

Data Fabrics Add Augmented Intelligence to Modernize Your Data Integration

Let's talk data

Data management teams are under constant pressure to provide faster access to integrated data across increasingly distributed landscapes. Data and analytics leaders must upgrade to a data fabric design that enables dynamic and augmented data integration in support of their data management strategy.
 

Want to talk with an analyst?

Best to hear it from the horses mouth.