Why Cloud Analytics is Better Analytics


Information is a strategic asset. Companies acknowledge that value and are collecting huge volumes of data, from all possible sources. But very few companies can leverage that data to their competitive advantage. Challenges range from data accuracy and completeness to speed and complexity of implementing analytics.

An even bigger issue is that, once implemented, analytics remains so disconnected from operations that it is almost irrelevant. The insights revealed are generally at an aggregate level and provide information that is merely “good to know” and seldom actionable by operational teams.

Today, cloud and mobile technologies are providing enterprises of all sizes with opportunities to use big data and analytics to make better, data-driven decisions. New-generation platforms (cloud, big data, analytics) bring analytics and operational applications together to deliver demonstrable ROI.

Cloud computing allows organizations to consolidate data from all sources, across all communication channels, and do it at a big data scale. Without cloud, collecting data from all internal applications, social networks, devices, and data subscriptions would be cost prohibitive for most organizations. On-premise big data deployments could involve significant operational risks and expensive infrastructure. The ongoing maintenance of on-premise systems itself would be daunting enough to discourage many organizations.

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Let’s consider some of the advantages that cloud offers over on-premise data analytics implementations.

Bringing together reliable data for analytics has always been a challenge. Analytics are not accurate if data is scattered, stale, and incomplete. Many of your applications and data sources, such as social and third-party data subscriptions, are in the cloud. In this environment, creating an on-premise data store is less than optimal. A cloud-based data management platform makes it easier for companies to blend data from all such sources and helps match, merge, and clean data. Real-time access to social and third-party data sources and real-time data stewardship enabled by cloud solutions keeps your data current, complete, and clean.

Once data is consolidated and cleansed, you can create a unified view of information that is readily available for your big data analytics. Now you can easily feed insights back into online data-driven applications. Because analytics and operations are running on top of the same data foundation, there is no mismatch, information gap, or time lag between the two.

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A modern data-management platform brings together master data management and big data analytics capabilities in the cloud so that business can create data-driven applications using the reliable data with relevant insights. The principal advantage of this unified cloud platform is faster time-to-value, keeping up with the pace of business. Whenever there is a need for a new, data-driven decision management application, you can create one in the cloud quickly. There is no need to setup infrastructure (hardware, operating systems, databases, application servers, analytics), create new integrations, or define data models or data uploads. In the cloud, everything is already set up and available. Use cases are limited only by your imagination. Sales operation teams can create better alignments and account planning applications, marketing teams can create segmentation for campaign planning, contact centers can uncover up-sell and cross-sell opportunities, and strategy groups can simulate pre and post-merger scenarios.

On-premise and disconnected systems make it tedious to develop analytical models collaboratively and to share the insights. Team members use emails and printouts to discuss ideas and consolidate feedback manually. Development takes time; many inputs are lost, and many members with valuable ideas are never included.

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