Explain cloud analytics.

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 Cloud analytics

  •  Cloud analytics is a marketing term for businesses to carry out analysis using cloud computing. It uses a range of analytical tools and techniques to help companies extract information from massive data and present it in a way that is easily categorized and readily available via a web browser.
  • Cloud analytics is a term for a set of technological and analytical tools and techniques specifically designed to help clients extract information from massive data.
  • Cloud analytics is designed to make official statistical data readily categorized and available via the user's web browser.
  • Cloud analytics is a service model in which data analytics and business intelligence (BI) processes take place on vendor-managed infrastructure rather than a company’s on-premise servers.
  • Because the analytics vendor or third-party partner typically manages setup and maintenance, cloud data analytics makes it easy for you to empower all employees with deep data insights through scalability, performance, reliability, and cost savings.
  • Cloud analytics is the process of storing and analyzing data in the cloud and using it to extract actionable business insights. Similar to on-premises 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.
  •  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.

Benefits of cloud analytics

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 makes 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.

 

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 percent 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.

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Cloud Analytics Benefits

Let’s dig deeper into the reasons why companies are moving their analytics processes to the cloud:

Lower Costs and Faster ROI: With cloud-based analytics, you’ll reduce the risk that comes with making upfront hardware investments for on-premise servers. In addition, because you won’t need in-house expertise to maintain servers and software, you’ll cut even more costs.

Power Remote and Hybrid Work. The workplace has changed, and your distributed workforce, as well as your suppliers and partners, need immediate, governed access to fully interactive analytics from anywhere and on any device.

Easy Collaboration: The best cloud analytics platforms allow you to take snapshots of analytics, add commentary for improved context, and tag in the discussions. This creates a collaborative canvas for both real-time and asynchronous decision-making.

Up-to-Date Capabilities: Updates and upgrades are performed automatically in cloud data analytics solutions. That means organizations save costs in the long run, as they don’t have to worry about ongoing maintenance associated with on-premise servers.

Flexible Performance: Rather than purchasing new hardware as your data needs change, cloud data analytics gives you the ability to turn services on and off as needed. For example, if you have a spike in data, you can quickly scale up your services, and then scale back down again when there’s less activity.

Reliability and Security. SaaS environments lower data security risk. First, the likelihood of error is far lower when servers aren’t manually configured. And second, SaaS security certifications require providers to meet stringent standards.

Centralized Data: When data is scattered and siloed across your CMS, ERP, marketing automation and countless other systems, it’s hard to get a complete view of your business. A cloud data analytics solution brings all of this data together to bring a complete picture of your business and maximize insights for everyone across the organization.



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