Are your customers data smart?
As the need to unlock the value of volumes of data for competitive advantage becomes increasingly critical, many of your customers now see creating an efficient and cost effective business intelligence (BI) model as a priority. With market research analysts predicting that the cloud analytics market will grow at a CAGR of approximately 21% until 2020, with 60% of respondents citing BI as a top driver for cloud (Nomura Research), this represents one of the biggest opportunities for Arrow partners today.
Let’s explore the business benefits of Cloud Data Analytics for your customers.
From data collection to analysis, the Cloud can really help to simplify and streamline the BI process - particularly if the data in question already lives in the Cloud. Whether it’s data from social media or IoT devices, cloud-based solutions enable organisations to store large volumes of data far more cost effectively. Having made that decision due to the cost benefits, it makes little sense to then spend time and resources moving the data on-premises for analysis!
Combining BI tools and techniques with cloud computing technologies can also enable IT and line of business leaders to collaborate more effectively. With less time wasted on both sides, sending data backwards and forwards, the business objectives from data analysis can be achieved far more quickly and efficiently.
Gartner estimates that 85% of Fortune 500 companies do not reap the full benefit of their big data analytics because lack of accessibility causes them to miss potential opportunities. As analysis moves towards the Cloud, employees can access company information remotely from any location, making data more accessible and driving greater value to the business.
What are the key use cases?
Social media data naturally lends itself to cloud-based analytics as it overcomes the difficulty of processing activity across different sites and servers. Cloud enables social media data from all locations to be analysed simultaneously, so intelligence can be gathered and acted upon far more quickly.
When data is stored and analysed in the Cloud, it enables your customers to run their businesses far more efficiently, due to the speed at which data can be recorded and processed. For example, companies can track the sales of an item from all their branches in real-time and adjust their production and shipments as necessary – remotely managing stock rather than waiting for inventory reports from area stores.
According to "Analytics in the Cloud" a 2015 report by Enterprise Management Associates, adopters of cloud-based analytics and BI solutions cite time-to-delivery as a key motivator, with financial drivers such as hardware and infrastructure cost, reduced implementation cost and reduced administrative cost, following closely behind.
How should I start the conversation?
Ask your customers what data they want to be able to analyse, how ‘big’ it is and where it’s currently located. You will also need to find out whether the processing of that data will be continuous, or on a less frequent ‘burst’ basis. You will then be in a position to develop the right technical approach, as well as addressing issues around data governance and security.
Don’t be afraid to ask the question and start the conversation about cloud with your customers. We’re here to support you all the way – from identifying opportunities to closing the deals.
Find out more about the Arrow Cloud Enablement Programme and how your business can benefit, or click here for information on attending our Cloud Leadership Forum on 1st November.
Are your customers ready for cloud infrastructure?
Do you feel like your customers are ready and able to deliver desktop-as-a-Services and Disaster Recovery through the Cloud?
Cloud Storage in the Microsoft Cloud
What has Microsoft done to alleviate concerns with cloud storage? David Nolan takes a look at Microsoft Azure.
Arrow Bandwidth Episode 10 – Big Data in Action with KnowNow
David and Rich are joined by Chris Cooper from KnowNow to discuss the real world outcomes of Big Data