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Cloud Analytics 101: Uses, Benefits and Platforms

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Cloud analytics is the process of storing and analyzing data in the cloud and using it to extract actionable business insights.

Simply one shade of data analytics, cloud analytics algorithms are applied to large data collections to identify patterns, predict future outcomes and produce other information useful to business decision-makers.

However, cloud analytics is generally a more efficient alternative to on-premises analytics — which requires businesses to purchase, house and maintain expensive data centers. While on-premises analytics solutions give companies internal control over data privacy and security, they are difficult and expensive to scale. Cloud analytics, on the other hand, benefits from the scalability, service models and cost savings of cloud computing.

Businesses generate terabytes of data in the course of daily operations. Today, most of this data — sourced from websites, social media, IT devices and financial software, among other things — exists in the cloud. Cloud analytics tools and analytics software are particularly efficient for processing these huge data sets, producing insights in easily digestible formats and creating insights from data in the cloud available on demand, resulting in a better and more streamlined user experience.

Cloud analytics tools and analytics software are particularly efficient for processing these huge data sets, producing insights in easily digestible formats on demand that result in a better and more streamlined user experience.

Cloud Analytics 101: Uses, Benefits and Platforms

Making use of cloud computing data

First, to examine how cloud analytics work, you have to start with a cloud computing model.

In the cloud computing model, organizations can rent the IT infrastructure and services they need on-demand from a cloud service provider instead of purchasing and operating their own data centers. These services include everything from essential infrastructures like networking, servers, storage, databases, and software to advanced tools such as artificial intelligence (AI) and machine learning systems.

Cloud computing allows organizations to

  • Reduce costs
  • Increase productivity
  • Avoid high equipment costs
  • Scale resources according to variable business needs
  • Remotely access systems from any web-enabled device.

While making use of all of those benefits, cloud computing produces an immense amount of data — making it one of many reasons we have access to more data than ever. Not making use of that data can cause organizations to miss out on major insights or key performance indicators.

That’s where cloud analytics comes in.

How does cloud analytics work?

In cloud analytics systems, all generated data is collected and securely stored in the cloud, where it can be accessed from any internet-connected device. The cloud analytics system can then clean, organize, process, and analyze the data using proprietary algorithms. These insights are presented to the user through different data visualizations and other intuitive formats.

Each cloud analytics solution comes with its own particular set of features, but all solutions have several common components. According to Gartner, these include the following:

  • Data sources: These are the various sources from which your business data originates. Common examples include web usage and social media data, as well as data from CRM and ERP systems.
  • Data models: A data model structure retrieves data and standardizes how data points relate to each other for analysis. Models can be simple — using data from a single column of a spreadsheet, for example — or complex, involving several triggers and parameters, in multiple dimensions.
  • Processing applications: Cloud analytics uses special applications to process huge volumes of information stored in a data warehouse and reduce time to insight (more on this below).
  • Computing power: Cloud analytics requires sufficient computing power to intake, clean, structure and analyze large volumes of data.
  • Analytic models: These are mathematical models that can be used to analyze complex data sets and predict outcomes.
  • Data sharing and storage: Cloud analytics solutions offer data warehousing as a service so that the business can scale quickly and easily.

In addition to these features, AI is becoming a more integral part of cloud analytics. Machine learning algorithms, in particular, enable cloud analytics systems to learn on their own and more accurately predict future outcomes.

Cloud analytics benefits

Cloud analytics comes with many advantages for the enterprise. Here are a few benefits with the biggest impact on your business.

Data consolidation

Big data produced from numerous, disparate sources across the organization can make it nearly impossible to get a unified view.

Cloud analytics brings all of a company’s data sources together to produce a more complete picture. All stakeholders, regardless of their physical location (or the data’s location), can easily access this data in one place, to gain more accurate insights and make better business decisions in real-time.

(Read about real-time data and data streaming.)

Sharing and collaboration

Big data siloed in individual departments such as finance or human resources affect the whole business. A cloud analytics solution can better integrate the data from different parts of the organization — subject to configurable role-based access controls — leading to better communication and decision-making.

Scalability

When workloads and data volumes grow rapidly, administrators running on-premise platforms have to purchase and install new hardware to accommodate the rise in demand — a service model that often leads to over-provisioning and expenses that can seem unnecessary if demand falls in the future.

With cloud analytics services, organizations can scale up to accommodate spikes in demand by bringing more instances online (or reducing them when demand dips) and paying only for what they use.

Cost reduction

In addition to the costs of the various hardware requirements, on-premise platforms need frequent upgrades and migrations, invariably leading to system downtime affecting business continuity. On-premise analytics also necessitate specialized skill sets that some organizations don’t or can’t afford to have in-house.

With cloud analytics, organizations aren’t required to purchase and support additional hardware, and can also avail the in-house expertise of service providers.

Security

Security monitoring is usually just one of the many areas that an organization’s IT staff is responsible for, but it’s a full-time focus for cloud hosts. Cloud analytics providers also use robust encryption to secure data as it is transmitted over networks.

But the biggest security advantage they offer may be simply that the data is stored offsite: A recent report found that 34% of all breaches happened as a result of insider threat actors, including current and former employees who take classified or proprietary information with them when they leave the company.

Cloud Analytics 101: Uses, Benefits and Platforms

How to choose the right cloud analytics platform

Not all cloud analytics platforms are created equally, so it will pay off in the long run if you take time to identify your organization’s particular needs before making a purchasing decision. Some key factors to consider include:

  • Scalability. A good cloud analytics platform will be able to accommodate your growing business and its data needs. Flexible pricing plans will allow you to pay for only the resources you use.
  • Security. While nearly all cloud providers encrypt data as it’s moving over a network, many do not secure data when it is just sitting in storage. Look for a platform that encrypts data both “in transit” and “at rest.”
  • Real-time integration. Your cloud analytics platform should integrate in real-time with your organization’s other systems so your company can stay up to date without any extra effort.
  • Analytics features. Every company is guided by unique business metrics. Look for a cloud analytics platform that is capable of calculating yours.
  • Responsive interface. Data analysis is run on mobile devices more and more. Make sure any cloud analytics platform you’re considering isn’t going to bog down on users’ smartphones and tablets.

Put your cloud data to work

Your business is churning out an extraordinary amount of data every day.

Cloud analytics presents an irresistible opportunity to consolidate that data and turn it into actionable intelligence while simultaneously reducing procurement and maintenance costs. The key is to determine your business needs ahead of time so you can maximize the cloud analytics platform of your choice. The insights you need to give you a competitive edge and move your business forward are in front of you — cloud analytics gives you a way to put them at your fingertips.

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This posting does not necessarily represent Splunk’s position, strategies or opinion.

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