Solutions and market for DaaS by Sector, Collection Type, Source Type, and Data Structure
SEATTLE, WASHINGTON, UNITED STATES, October 9, 2018 /EINPresswire.com/ — As part of the overall global trend towards business and government digital transformation, there is an increasingly expansive amount of enterprise and industrial data generated but not optimally utilized. This data is rendered more readily usable in a Data as a Service (DaaS) cloud-based services model.
Investigating the Data as a Service market from two different perspectives, recent Mind Commerce research provides analysis of both enterprise DaaS solution/service usage as well as syndication of their own data as a means of monetization. All major sectors are covered including Enterprise, Industrial, Consumer, and Government. The study takes into account Public, Business, and Government data defined as follows:
Public Data: Consists of Communications and Internet Data (broadcast media, social media, texting, voice, video/picture sharing, etc.), Government Tracked Data (public records such as vehicle and home title, licensing, public resource usage including roadway usage), User Generated Data (consumer and business data made public [may be anonymized or not] such as vehicle usage, appliance data, etc.), and Other Data category.
Business Data: Consists of Enterprise Data and Industrial Data across various industry verticals. This data comes from many different business related activities. Some of this data may be static and/or stored in data lakes. Some of this data may be generated and used in real-time.
Government Data: Consists of data that the government collects about itself such as Government Services Administration (GSA), essential services (such as public safety), military, homeland security, etc. This is not to be confused the government collecting certain public data (such as highway usage).
Research findings indicate that many would-be enterprise data users are unaware that they can potentially acquire anonymized data originally sourced from other companies as well as government and public sources. There is also a lack of awareness that DaaS solutions may include a hybrid mixture sourced from a given business own data as well as other companies' data, government and public data. This research has also identified a general lack of awareness of opportunities for enterprise to syndicate their own data as a means of monetizing their digital assets.
A key area for both data acquisition and data usage, Internet of Things (IoT) data is growing nearly three times as fast as non-IoT DaaS, with much of it streaming data that will benefit from advanced real-time analytics software and platforms. Machine-sourced data is growing twice as fast as non-machine data, largely due to IoT apps and services. Data as a Service platform configurations that utilize Artificial Intelligence (AI) algorithms will add further value to enterprise via AI enabled value-added services such as “Decisions as a Service”.
The Mind Commerce, Data as a Service market report, Data as a Service (DaaS) Market: Enterprise, Industrial, Public, and Government DaaS 2018 – 2023, evaluates the technologies, companies, strategies, and solutions for DaaS. The report assesses business opportunities for enterprise use of own data, others data, and combination of both. The report also analyzes opportunities for enterprise to monetize their own data through various third-party DaaS offerings. The report evaluates opportunities for DaaS in major industry verticals as well as the future outlook for emerging data monetization. Forecasts include global and regional projections by Sector, Data Collection, Source, and Structure from 2018 to 2023.
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Mind Commerce is an information services company that provides research and strategic analysis focused on the Information and Communications Technology (ICT) industry. Our ICT reports provide key trends, projections, and in-depth analysis for infrastructure, platforms, devices, applications, services, emerging business models and opportunities.
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Source: EIN Presswire