Data has always been essential to improving decision-making for many companies. Each company has a lot of data generated by different areas such as interactions with suppliers, partners and customers but also by several processes and tools to support, inside the company but increasingly also outside the company through numerous applicatives and/ or tools and/ or generic touchpoints.
The main challenges are that data is often heterogeneous and stored in different formats, or in systems that do not communicate with each other. Data analysis also requires storage space and considerable computing power, making it difficult to justify the initial investment and leading to a further slowdown in progress.
Amazon Web Services (AWS) cloud services provide all the tools you need to deploy, maintain and scale a complete Business Intelligence and Business Analytics infrastructure.
Why managing Data in the AWS Cloud
Availability of a Cloud Computing infrastructure
With Amazon Web Services, you have access to a globally distributed Cloud Computing infrastructure across multiple fully managed regions, designed to easily scale storage resources, provide a high level of security and resilience, and accessible directly from the internet. The AWS cloud provides scalable storage and performance that automatically adapts to your needs while minimizing manual administration tasks.
Cloud Computing services can be divided according to the type of provisioning offered.
- Infrastructure as a Service (iaas) refers to services that offer facilities for computing such as virtual machines (Amazon EC2) and storage (Amazon S3).
- Platform as a Service (PaaS) refers to platforms to build and implement applications. Some examples are AWS Elastic Beanstalk, which allows you to deploy and manage applications such as websites, or AWS Lambda to run code in a serverless manner.
- Software as a Service (SaaS) are the software applications already built and directly usable. Some examples are Amazon QuickSight and Amazon SageMaker.
"On demand" resource management
AWS cloud infrastructure is based on “on demand” resource management, so the computational power and storage used are adapted to the needs of the moment, without incurring in the typical cases of over/under dimensioning of the resources of the infrastructures “on-premise” (in loco).
The cloud is the most economical way to achieve business objectives: the costs of services follow the “pay-per-use” paradigm, so only the costs of the services used for the actual time in which they are used are charged, with granularity of the second. This eliminates initial investment costs and fixed maintenance costs, as all data centers are entirely managed by Amazon.
Security is a key element for managing data in the cloud, so AWS provides encryption services (AWS Key Management Service) and virtual private networks (Amazon VPC). In addition, all actions on the services can be monitored and recorded via Amazon CloudWatch and AWS CloudTrial.
AWS: Data Storage and Consolidation
AWS facilitates data consolidation with flexible services to store heterogeneous data and create data warehouses.
- Amazon S3: Amazon S3 is a virtually unlimited object storage service, providing scalability, flexibility and data availability. S3 is the ideal, low-cost solution for storing and reading all kinds of data. It can be easily integrated with other AWS services to speed up and simplify data processing and analysis. It also lets you create Data Lake.
- Amazon Redshift: Redshift is a solution to easily create and manage scalable Data Warehouse which can be used to store large amounts of data (petabytes) and is natively integrated with reporting and BI tools.
AWS also provides other database types, suitable for every need. Some examples are Amazon RDS for relational database and Amazon DynamoDB for NoSQL database.
AWS: Data Analysis and Visualization
AWS offers several fully managed services that allow companies to explore their data and create interactive reports.
- Amazon Athena: Athena is an interactive query service fully managed by AWS, which allows you to query data saved in S3 via SQL queries. It is the ideal solution to quickly analyze large amounts of data on S3.
- Amazon Quicksight: Amazon Quicksight is a cloud-based Business Intelligence service that can be used to create interactive dashboards and graphical elements for browsing and viewing data. It is natively integrated with S3, Redshift and Athena.
AWS: Data workflow with ETL processes
AWS simplifies the data loading and transformation processes that are used for Business Intelligence.
- AWS Glue: AWS Glue is Amazon’s specific ETL (Extract, Transform, Load) service that is used to extract, transform and save data from different and heterogeneous sources, and is natively integrated with other AWS data storage services, such as S3 and Redshift. Building data pipelines is very easy thanks to the advanced features of AWS Glue, such as automatic generation of ETL code to apply transformations on data.
- AWS DataBrew: AWS DataBrew is a visual data preparation tool. You can import a database or file to get real-time statistical information and apply predefined data transformations.
AWS: AI & Machine Learning
Business Intelligence processes can be reinforced by the use of Artificial Intelligence (AI) and Machine Learning (ML), which allow to extract even more significant information from data.
- Amazon SageMaker: Amazon SageMaker allows you to easily build, train and implement machine learning models. The service includes a suite of algorithms and frameworks already implemented, which can also be adapted ad-hoc for the data that you are analyzing. Some of SageMaker’s business intelligence applications are predictive analytics, anomaly detection, and customer segmentation.
Amazon also offers intelligent application services (AI-powered) for many use cases, such as Amazon Rekognition for image recognition, and Amazon Polly for creating Chatbot.
Blue BI & AWS
The goal of Business Intelligence (BI) and Business Analytics (BA) is to analyze data to identify relevant information, identify new opportunities and accelerate growth through informed decisions. Today’s digital transformation drives operational efficiency and competitive differentiation in the market, as relying on outdated or incomplete data can create inefficient strategies.
Blue BI is focused on developing competitive and efficient solutions to integrate Business Intelligence and cloud and promotes the use of AWS to address the challenges of data management and analysis.
Contact us to understand how Blue BI can help you implement the use of AWS services.