Build, protect and deploy apps across any platform and mobile device
Leverage a complete UI toolbox for web, mobile and desktop development
Automate UI, load and performance testing for web, desktop and mobile
Rapidly develop, manage and deploy business apps, delivered as SaaS in the cloud
Automate decision processes with a no-code business rules engine
Build mobile apps for iOS, Android and Windows Phone
Deploy automated machine learning to accurately predict machine failures with technology optimized for Industrial IoT.
Optimize data integration with high-performance connectivity
Connect to any cloud or on-premise data source using a standard interface
Build engaging multi-channel web and digital experiences with intuitive web content management
Big data volumes are growing exponentially, making it all the more important for firms to access, integrate, and analyze it. Currently 85% of Big Data is on premise, but with the increasing availability of Data as a Service (DaaS) and the Cloud, this trend is likely to change.
Enterprises generally keep consumer and business intelligence data on premise. It is all essential to measuring performance and providing key insights, but what happens when you want to compare the hard-earned data you mined to external, third-party sources? DaaS providers allow you to integrate this external data without storing it on-premise or gathering it on your own.
For example, when integrating weather data with Sales data in order to gain insights over time, keeping an on premise, real-time database is not very feasible or practical. Integrating this data from a real-time weather data provider saves time and makes analysis all the more accurate.
Recent advances in Big Data such as Hadoop, MongoDB, and Spark SQL are offering real-time data access from any place at any time. This allows DaaS providers to enable data access to more data sets than ever before, whether free data from government organizations or premium data. Rather than finding on premise storage space, DaaS providers allow real-time cloud access, which is especially attractive if this data is not needed long term. This allows for data to be packaged by volume, type, or specificity to better account for consumer needs and price points.
Big Data continues to grow and change in its role in all kinds of industries and enterprises, creating a specific need for tailored approaches for every business. As huge amounts of data are mined from the IoT and consumers, storing and analyzing all of it becomes a daunting task. DaaS allows for business intelligence and analytics to be preformed for any period of time, anywhere from the cloud. The time of massive, unsearchable on-premise data lakes is over and the DaaS revolution has arrived.
Austin is a content strategist, social promoter and marketer at Progress with a passion for technology, data visualization and music. He keeps up to date on the data connectivity industry and discusses related topics in a visually appealing, thorough and easily understandable way.
Copyright © 2017 Progress Software Corporation and/or its subsidiaries or affiliates.
All Rights Reserved.
Progress, Telerik, and certain product names used herein are trademarks or registered trademarks of Progress Software Corporation and/or one of its subsidiaries or affiliates in the U.S. and/or other countries. See Trademarks for appropriate markings.