Better ways to use data and get the insights and answers you need is possible with The Wizard

What do you do with the data you have? How is it helping you do more with your business? How is it helping you to drive innovation or stay ahead?

These are the things organizations need to start asking themselves and we are here to help you get the insights and the actions you need to help you solve those questions.

Fast access to flexible and low cost IT resources, on the most complete platform for big data. We can help you get there.

Immediate Availability

Most big data technologies require large clusters of servers resulting in long provisioning and setup cycles. With AWS you can deploy the infrastructure you need almost instantly. This means your teams can be more productive, it’s easier to try new things, and projects can roll out sooner.

Broad & Deep Capabilities

Big data workloads are as varied as the data assets they intend to analyze. A broad and deep platform means you can build virtually any big data application and support any workload regardless of volume, velocity, and variety of data.

Trusted & Secure

Big data is sensitive data. Therefore, securing your data assets and protecting your infrastructure without losing agility is critical. AWS provides capabilities across facilities, network, software, and business processes to meet the strictest requirements. Environments are continuously audited for certifications such as ISO 27001, FedRAMP, DoD SRG, and PCI DSS. Assurance programs help you prove compliance with 20+ standards, including HIPAA, NCSC, and more. Visit the Cloud Security Center to learn more.

3 V's of Big Data



Over the years the sheer amounts of data ingested and available for consumption has skyrocketed organizations struggle on what to do with what they have and how to make sense of it all


Organizations now have options for getting insights and answers from information as it is streamed in real time this has great implications for organizations as now we are now able to move from batch processing to delivering results based on live data. This improves the decisions we are able to make and deliver with speed.


We recognize the difficulty organizations have had with being able to process data from multiple sources in multiple formats. This can be a headache and we have solutions that allow for streams of data from multiple sources and can transform it for easy consumption for your BI, AI,  and ML tools to ingest and deliver the insights you need.

Machine Learning

Amazon Machine Learning is a managed service that provides visualization tools and wizards that guide you through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology.

Amazon Redshift

Easily provision, configure and deploy a data warehouse within minutes. Amazon Redshift handles all the work needed to manage, monitor and scale it.

Amazon Quicksight

We use Amazon Quicksight to help get deep visualizations into the data and can easily arrange it to get us the right information quickly at a fraction of the costs.

Big Data Frameworks
We can help you take advantage

Hadoop & Spark

                   Amazon EMR

We can help you easily provision a fully managed Hadoop framework in minutes. Scale your Hadoop cluster dynamically and pay only for what you use. Run popular frameworks such as Apache SparkApache Tez, and Presto.

Interactive Query Service

    Amazon Athena

Easily analyze petabytes of data in Amazon S3 using ANSI SQL. With Amazon Athena, there are no clusters or data warehouses to manage, so you can start analyzing data immediately. You don’t even need to load your data into Athena, it works directly with data stored in S3.


Amazon Elasticsearch Service

Setup and deploy an Elasticsearch cluster in minutes, using a web-based console. Seamlessly run your existing Elasticsearch applications using the Elasticsearch open-source API.

Scale your business and process big data workloads in less time and at a lower cost on demand

Big Data Workflow


Collecting the raw data – transactions, logs, mobile devices and more – is the first challenge many organizations face when dealing with big data. A good big data platform makes this step easier, allowing developers to ingest a wide variety of data – from structured to unstructured – at any speed – from real-time to batch.


Any big data platform needs a secure, scalable, and durable repository to store data prior or even after processing tasks. Depending on your specific requirements, you may also need temporary stores for data in-transit.

Process & Analyze

This is the step where data is transformed from its raw state into a consumable format – usually by means of sorting, aggregating, joining and even performing more advanced functions and algorithms. The resulting data sets are then stored for further processing or made available for consumption via business intelligence and data visualization tools

Consume & Visualize

Big data is all about getting high value, actionable insights from your data assets. Ideally, data is made available to stakeholders through self-service business intelligence and agile data visualization tools that allow for fast and easy exploration of datasets. Depending on the type of analytics, end-users may also consume the resulting data in the form of statistical “predictions” – in the case of predictive analytics – or recommended actions – in the case of prescriptive analytics.

How far do you want to go?

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