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Gartner Hype Cycle Data Management 2021

Gartner Hype Cycle Data Management 2021 700 460 Nicola Lapenta

Gartner 2021 Analytics for Data Management

Table of contents

Introduction

If you as a business owner or manager are interested in implementing effective and lasting data services, Gartner analysis can help you understand the evolutionary pace of emerging and maturing technologies offered by leading vendors. This article summarizes the guidance for data management solutions found in the Hype Cycle report for 2021.

The Gartner Hype Cycle Model

The Hype Cycle model is a methodology developed by Gartner, an information technology consulting research and analysis firm, to graphically represent the maturity, adoption and application of specific technologies.

The curve indicates what type of technology is worth adopting and the time frame in which it should be considered by reporting information on two variables: time on the x-axis and usage expectations on the y-axis.

The first part of the curve, the highest peak, shows the areas of highest media uptake. The prospects listed are new and potentially high, but also unknown because they are not yet used in the market, so the risks are also relatively unknown.

As a technology moves through the hype cycle, the costs and benefits become clearer and more defined, which in turn makes the solutions to be adopted less risky. Some technologies will move quickly as they are deployed while others will stop and be abandoned.

Gartner Hype Cycle for Data Management

The Gartner report for Data Management technologies (Figure 1) clearly shows that investing in a Data Virtualization service today allows you to take advantage of a mature service that creates value for the organizations that adopt them.

Gartner hype cycle for data management report
Figure 1 Gartner Hype Cycle Data Management 2021

It is an important asset because it allows organizations to quickly connect, integrate and deliver data without additional replication or the creation of multiple separate silos. Data virtualization, significantly improves the flexibility to integrate new data sources. It is also recommended as an indispensable component to help optimize costs since it is not managed or stored locally.

Data virtualization is beneficial for data engineering teams that want to gain rapid access to data sources and need cost-effective management.

Data as a Service (DaaS) solutions, services that go beyond simply displaying reports and dashboards, are becoming increasingly popular among data management services to help organizations make effective decisions. You might also be interested in these articles on this topic:

The benefits of DaaS – Data as a Service

How to start using DaaS services – Data as a Service

Conclusions

I believe that the adoption of data services for any size of online business is of strategic importance, especially if adopted for a long period. The evolved management of data services largely repays the investment in a reliable way and responds to new analytical and reporting requirements to implement effective digital strategies.

Published by: Nicola Lapenta

Credits:  Gartner

Photo by: Wikipedia