Cloud data services: new ways to create value

Cloud data services are growing extremely rapidly as users around the web utilize the cloud to improve internal sharing, data analysis and grow the overall businesses. Optimizing cloud services is becoming more critical which has in turn made choosing rules regimes or self-service analytics very important. At the same time, data is growing exponentially which means that administrators must get a handle on their analysis methodology before the volume of data gets out of control.

Industry giants such as Salesforce and Zendesk are using cloud data services as well. Salesforce and Zendesk integration for third party standards is becoming the rule rather than the exception.

Two major cloud service types

In fact, more and more companies are turning to cloud services to help analyze data. The two major types of cloud data services include self-service analytics and rules regimes. Self-service analytics services (sometimes know as self-service business intelligence) provide a business with the capability of searching, analyzing and reorganizing all of their own data. DataHero is one third party self-service business intelligence platform that allows users to create marketing dashboards and complex computations on data. The software integrates with most major cloud data platforms.

On the other hand, rules regimes set limits, goals or decision points in which the software will automatically analyze data. A common technique is the IFTTT (“If this, then that”) rule in software. When a limit (such as a sales goal) is achieved, an email or alert will be created. Companies or individuals who have long-term or short-term goals can easily set rule regimes to help indicate when those goals are achieved and create a standardized analysis. Zapier is a service that allows IFITT processes such as sending a Tweet when your fitness wearable device reaches a goal.

Salesforce and Zendesk use cases

Salesforce and Zendesk both utilise cloud data services in both ways to enhance the user experience. For example, Informatica is a third party app that integrates with Salesforce. The software is a self-service analytics tool that allows users to cleanse, standardize, de-duplicate and consolidate data before providing it for analysis. Salesforce has also built-in apps to provide rules regime capabilities for users when events occur such as closing deals, adding new leads etc.

Customer service software Zendesk similarly has self-service business intelligence and rules regimes apps. Zendesk Labs integrates with thousands of third party apps and also allows users, employees or companies to plug and play.

Cloud service architecture

However, building these cloud data services is not so simple. Cloud data systems originally were designed for single individuals or small groups to access data online through a single interface. Today’s cloud data solutions must address the problem of many thousands or even millions of users in different geographies accessing one platform with potentially millions of different data inputs that are changing dynamically.

Advanced architecture is required to handle these new demands on the systems. Some cases such as large retail stores have or large social networks have millions or billions of data constantly incoming to the company. Analyzing this data in the traditional way is simply unworkable, which has given rise to this new industry.

New entrants

As the industry becomes more complex, new companies are popping up to handle cloud data services problems. Segment.io recently raised a US$15-million Series A round of venture capital funding to provide software developers with one application program interface (API) that integrates over 100 solutions onto one platform. Developers that have been building for Zendesk and Salesforce will now be able to use those services on many different platforms.

The traditional big data industry will remain the largest single segment of the data industry. Software such as Hadoop is already mature with a huge community of users and developers. However, cloud data continues to grow at a rapid pace. As more data is stored in the cloud, these types of services will become more and more critical to business and productivity.

Consumer use cases

Even regular consumers will start to use cloud data services to analyze personal habits such as their personal Tweets, emails, fitness habits, sleep patterns, financial activity and other every day actions. Users can utilize both rule regime software or self-service analytics to gain deeper insight.

This industry will continue to grow, not only for regular consumers and small organizations but for large organizations as well. Large companies and platforms such as Zendesk and Salesfore that have massive cloud data services needs.