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Evolution of Cloud Analytics

Moving data to the cloud, once considered a strenuous task, has now become commonplace in most industries. Originally, this migration started as organizations looked to speed up the time needed to deploy applications or services – something that would typically take months or years using a conventional in-house IT approach. As the Line of Business (LOB) required a more responsive approach and a quicker time to market, companies looked to the cloud to circumvent some of the delays caused by their own IT departments.

Understanding the evolution of cloud analytics

The next wave of cloud migration is security and data protection; now that we are using the cloud, IT security is needed to protect that data. While some customers started to require strict security models to mimic their own, in many cases, the cloud vendors provided security that was as good (or better than) the customers’ own security. However, this led to customers having to meet compliance restrictions not only on their in-house systems but also for data held in the cloud. As a result, customers started to ask for analytics similar to their existing in-house controls.

Enter the compliance and governance of data – the third wave of evolution. This relates to who has access to what data and when they access it. Additionally, users expect to be able to access their reports and data on their cloud applications (like they would be able to on their own systems), something that was sadly lacking on most cloud applications.

As many of the cloud applications collect huge volumes of customer data (a.k.a. big data), enterprises are demanding the ability to report and run analytics in real time on the cloud data. This has led vendors to either provide reporting and analytics that are directed at the business user, or they must open up access to the data via APIs to allow customers to create custom reports or interfaces to extract or analyze data in volumes never seen before.

What data can be pulled from cloud analytics and used to improve customer experience?

Big data Infographic

(Image Source: Domo)

Organizations using cloud analytics can use the data to improve customer experience. With the move to digital transformation, organizations are delivering new and improved services to their customers. Therefore, most of the analytics being tracked are customer experience-related, including:

  • What the customer experienced: these include transaction times and the number of clicks; ease of access of data, time to buy, what the customer accessed and how often. This also includes customer profile information and how to build an ongoing profile of the customer.
  • The IT experience and what controls are in place: customers want to know where their data is and if organizations are able to control and protect it. Organizations are asked to report who has access to this data and when they accessed it. Also of concern is whether users have been deprovisioned after they have left the company and had their access revoked.
  • The cost experience: Due to the rapid adoption of cloud services, many organizations are facing the challenge of managing licenses. In the old model, purchasing was done centrally and licenses were typically managed by IT and procurement centrally. Now, end users are buying cloud services, which often results in a lack of central controls.
  • IT is demanding analytics on their own users including:
    • Who has licenses?
    • What type of license?
    • Have they used it? When? For how long?
  • The growth experience: The amount of data being created is driving organizations to look at future trends to identify growth opportunities for the business. Since this is not typically an out-of-the-box feature, vendors are being pushed to provide custom access to cloud data to allow analytics to be run on the fly.

Prior to cloud analytics existence, what was used to improve customer experience?

In the past, the customer experience was typically measured by IT system service level agreements (SLAs) – for example, was the website up and working? Other metrics included network response times and click times for web access. However, this data is nowhere near as sophisticated as the data now being captured and reported on today. Often, this data was held in disparate systems, therefore many sources had to be combined to provide meaningful data.

How are users accessing cloud analytics?

There are four main ways users are accessing data from the cloud:

  1. Using out of the box capabilities and reports supplied by the cloud vendor. These often contain sufficient data and are being improved constantly by the vendor.
  2. Accessing centralized data repositories supplied by the cloud vendor which often have intuitive interfaces to query the data.
  3. Importing data to familiar desktop tools that the customer already uses and is familiar with. E.g. Excel, Tableau, etc.
  4. Through custom interfaces built with APIs, which allow organizations to serve up the data to their users in a familiar, intuitive manner. There are many tools out on the market that end users are familiar with today and IT is being asked to build interfaces from the cloud to make that data readily available.

Who benefits most from the improvements?

The end customer and the organizations are the main beneficiaries. As access to data speeds up delivery of new business services, it also provides a better customer experience which results in improved customer loyalty. In addition, internal IT can reduce costs and improve efficiencies, thus enabling the business. The ability to capture and utilize cloud data and analytics is enabling significant business growth.

By Daren Glenister

Daren Glenister

Daren is the Field Chief Technology Officer for Intralinks. Daren serves as a customer advocate, working with enterprise organizations to evangelize data collaboration solutions and translate customer business challenges into product requirements.

Glenister brings more than 20 years of industry experience and leadership in security, compliance, secure collaboration and enterprise software, having worked with many Fortune 1000 companies to turn business challenges into real-world solutions.

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