Analysing big data gives companies insights that can have immediate and dramatic impact on their business, and this is why so many companies are now doing it. Having those insights gives you the edge over your competitors and provides a more complete picture of your business. However, to carry out big data analytics you need the computing resources in place for it to be done effectively. In this post, we’ll explain why we think the best solution is cloud analytics.
What is Cloud Analytics?
Cloud analytics is a cloud-based solution which enables businesses to carry out analysis or intelligence procedures through integrated cloud models, such as hosted data warehouses, SaaS business intelligence (BI) and cloud-powered social media analytics. 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 categorised and readily available via a web browser.
Unified Vision of the Business
One thing that causes problems for many companies is when different elements within the organisation have disparate perceptions of what is going on. They are all working from their own data sets and no-one has the big picture.
A crucial advantage of using cloud analytics is its ability to consolidate big data from all sources and communication channels that a company employs. The capacity that cloud offers allows everything to feed in: you can gather large-scale data from all your internal apps, devices, social networks and data subscriptions – something which would be difficult to achieve in-house.
Using a cloud-based data management platform lets you easily blend data from a range of sources, enabling it to be matched, merged and cleansed – the result being far more accurate results that enable you to have a unified vision of your business. This vision can then be shared across the organisation so that everyone has the big picture.
The key to ensuring everyone sees the unified vision lies in the smooth accessibility that cloud-based data management platforms provide. Compared to in-house applications which have always been slow for companies to adopt, cloud-based apps are much easier to use and, in many cases, can be self-taught, reducing the need for staff training.
And because employees don’t need to create one-off reports or log into separate systems to undertake analytics, the technology is adopted more quickly throughout the company; analytics, therefore, becomes more accessible to everyone.
Take-up is improved even further when the apps that carry out the analytics also present the findings – as with Elastic Stack. Of course, being cloud-based, the applications are easily accessible to staff wherever they are and at any time, provided they have an internet connection.
Many companies find it a challenge to build a system that lets team members collaborate effectively. Using a mix of in-house and external systems can make it hard to develop analytical models and share the results. As a consequence, development lacks pace, work is often duplicated and not everyone gets to contribute their ideas – especially when a team is distributed across a wide geographical area.
This is not the case with cloud-based data analytics. Instead, teams can work together to curate data, create analytics designs and evaluate outcomes – no matter where they are based. Importantly, each member has access to real-time insights which can be acted upon instantly. This can be of real benefit for operational teams who need those insights to make critical decisions for the business.
The scrutiny faced by cloud service providers, as well as the international standards they need to comply with, ensures that they take security very seriously. Indeed, most public cloud providers have better security mechanisms in place and are much better at systemic security services than company managed, in-house systems.
In-house systems typically use a mix of older technologies and legacy apps that have more vulnerabilities than the state of the art systems found in cloud data centres. In addition, cloud systems have less complex architecture, making them easier to monitor and defend.
Another security advantage of the cloud is its ability to help companies meet recovery time objectives and recovery point objectives in the event of a disaster. Giant backup storage capacity and huge numbers of redundant failover servers make this easy for them to do, for most businesses this would be an extremely expensive undertaking.
From reading this article, you should now have a better understanding of how cloud computing can be of significant benefit for companies needing to undertake big data analytics. In particular, you will know how cloud analytics provides a unified view of the business and leads to better accessibility and collaboration for your teams. At the same time, it also proves a more secure environment in which to carry out analytics.
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