The world of big data analytics has revolutionized both the quality and quantity of insights generated by enterprises. Typically, legacy data analytics was performed manually by a dedicated analytics team, which would analyze the raw data and attempt to identify correlations that could then be used to direct your business trajectory.

With the introduction of the cloud, independent software vendors (ISVs) have started integrating automation into their analytics tools, negating the need for human input. This is great for businesses, as it reduces the risk of human error and increases the quantity and quality of insight generation through faster data processing.

Trianz experts have been at the forefront of this cloud analytics revolution. Our data analytics experts deliver the latest analytics automation consulting services on AWS, thanks in part to our Advanced Consulting Partner Status on the platform.

Automated data analytics and TCO calculation on AWS with Trianz

Trianz is a leading data analytics assessment and implementation provider that has helped hundreds of our clients to leverage analytics functionality on the AWS cloud. Our experts can design efficient, automated analytics solutions, leveraging the latest technological advancements in the field.

We offer a range of automated data analytics services and TCO calculation services on AWS, including:

  • TCO forecasting – Your enterprise wants to leverage the benefits of cloud data analytics, but it can be challenging to determine the costs in advance. This could result in a lower return on investment (ROI) than you hoped, increasing the risk of a project being classed as a failure in the eyes of key stakeholders.

    Trianz experts have developed a proprietary TCO calculator, purpose-built for the AWS cloud platform. This calculator can analyze your existing analytics solution and determine the costs of lifting and shifting it to the AWS cloud. This will ensure that you have a full understanding of the project costs, allowing you to better plan IT budgets.

  • Automated BI – Cloud-native data analytics has many use cases, with one lucrative option being business intelligence (BI). BI is used to generate actionable insights that direct your corporate strategy. These insights can help you build a leaner, more agile business model that increases your competitiveness in the global market.

    Besides Amazon Elastic MapReduce, you also have the AWS-native services like Amazon RedShift that leverages the Amazon Simple Storage Service (Amazon S3), offering numerous data storage performance tiers for different use cases. Our experts can point your data analytics tools at Redshift, leveraging the immense speed improvements on the platform and bolstering your BI generation capabilities.

  • Machine learning BI insight – The cloud has prompted the creation of numerous artificial intelligence (AI) and machine learning (ML) BI tools. AWS offers Amazon QuickSight, an ML-powered business intelligence service that simplifies insight distribution across the business. Visualized analytics lower the barrier of entry to information, helping you form a cohesive, data-driven business culture.

    Our experts can help you move to the fully-managed Amazon QuickSight platform. Analytics dashboards on the platform offer data visualizations in the form of graphs, pie charts and other easily understood formats. These can be easily shared and embedded into your enterprise applications, portals and websites.

Save Money While Performing Automated Analytics in Real-Time

AWS is the perfect platform for automated data analytics—with low-cost data storage solutions and task-specific compute nodes that negate the need for IT operations management (ITOM) workloads.

An automated analytics platform on AWS comes with many benefits, including:

  • Real-time insight – Automated data analytics on AWS generates actionable insights for enterprises in real-time. This service is offered natively on AWS through Amazon Elastic MapReduce, a serverless big data analytics platform that works with AWS Glue to automate extract, transform, load (ETL) workloads to generate such insights.

  • Cost savings – With data analytics on AWS, you can minimize operating costs when compared to on-prem thanks to the serverless nature of Amazon Elastic MapReduce. Serverless computing services only charge you for the resources you use with no additional charges. This is great for startups and SMEs that want to leverage data analytics but can’t afford the upfront cost for on-prem hardware.

  • Transparent pricing – When performing data analytics on AWS, you need to forecast the total cost of ownership (TCO) for budgeting purposes. Trianz has developed its own proprietary TCO calculator for data analytics workloads on AWS, so you can fully understand the costs before committing to a purchase.

Leverage AWS with Trianz

Big data analytics is expected to grow into a $40.6 billion industry by 2023, as more enterprises look to benefit from the insight generation capabilities of this technology. Our experts were at the forefront of the initial cloud revolution, and they are ready to help you leverage big data analytics on AWS. Implement big data analytics and improve your enterprise knowledge on AWS by getting in touch with our experts today.

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