The public cloud makes it possible for companies to use technologies such as Big Data to develop new business models and to generate growth. However, here companies are also facing the challenge of how to best use the new technologies for themselves and quickly get to market to keep from falling behind in the process of digitization. Storm Reply has many years of experience in the implementation and realization of the Big Data lifecycle as well as the corresponding technologies. Together with its sister companies, Data Reply and Concept Reply, Storm Reply is an ideal partner for your Big Data platforms.
Cloud computing makes it possible to inexpensively collect and process data in a previously unheard of scope. Cost-efficient processing of large amounts of data in the cloud offers companies new chances for growth. The cloud makes it possible to quickly provision and scale, which in turn makes it possible for companies to quickly react to changes in the market. However, many companies are now facing the challenge of competitively using Big Data technologies and advanced analytics tools.
By now, the offer from AWS extends beyond the provision of simple infrastructure services. More and more applications are being made available in the PaaS and the SaaS environment and these often represent the “state of the art” in their corresponding fields. This particularly applies in relation to application accessibility.
It is not enough to believe that the cloud is only a virtual computer center. This would prevent realizing the full potential of AWS. With “Right Platform Services”, AWS enables the use of a broad range of complex services that, until recently, were only available on the market with highly specialized and correspondingly expensive applications. As a specialist for all Amazon Services, Storm Reply can make these benefits accessible to their customers and support them in integrating the “Rich Platform Services” into their current application landscape.
Storm Reply has relevant experience in all phases of the Big Data life cycle. This includes data collection and streaming, storage, analysis and archiving as well as the expertise in RDBMS/DW/NoSQL etc. The successful implementation of big data pools and analytics tools makes Storm Reply an optimal partner for mid-sized and large companies in Germany and Italy – for the planning, the set up and the execution of your Big Data application platform. With its sister companies, Concept Reply and Data Reply, Storm Reply is optimally prepared to face the new challenges in the world of Big Data and the Internet of Things. AWS offers a broad selection of services for Big Data applications.
Amazon Web Services offers a broad range of services with which you can quickly and easily create and provide Big Data applications. AWS gives you fast access to flexible and inexpensive IT resources. You profit from fast scaling of practically all big data applications, including data warehouses, clickstream analysis, fraud detection, recommendation functions, event triggered extraction, transforming and loading, data processing without a server and IoT processing. AWS does not require any large preliminary time and cost expenses for the setup and management of the infrastructure. Instead you can provide the optimal resource types of the right size to execute your big data applications. You can almost immediately access as many resources as possible and only pay for what you use.
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Big Data on AWS
With the increase in data amounts, it is becoming more and more important to analyze and evaluate this in the scope of business intelligence as well as in real time. Amazon Machine Learning is a powerful tool that makes it possible to use machine learning algorithms for this purpose, without requiring long learning times or specialists. This makes it possible to track advanced predictive analytics or apply real time analysis approaches that make it possible for our customers to make more out of their data in a very cost-efficient manner. Storm Reply works very closely with Reply partners in this field to offer complex applications and to provision these for our customers. Machine learning is particularly suitable when linking to other AWS services – even if data are already in the cloud.
Amazon Machine Learning is a service that allows developers of all levels to easily use technology for machine learning. Amazon Machine Learning offers visualization tools and assistants that accompany you through the buildup process without having to learn complex ML algorithms and technologies. When your models are ready, you can use simple APIs with Amazon Machine Learning to call up prognoses for your application without having to implement user-defined prognosis codes or manage infrastructures. Amazon Machine Learning is based on the same practically-proven, high-grade, scalable ML technology that has been used for years in the internal community of Amazon data scientists. The service uses high-powered algorithms to generate ML modules by searching your existing data for patterns. Then Amazon Machine Learning uses these models to process new data and to generate prognoses for your application. Amazon Machine Learning is highly scalable and can generate billions of prognoses per day and provide these in real time and with a high throughput. No preliminary hardware or software investments are required to use Amazon Machine Learning. You pay for what you use, you can thus start small and scale when your application grows. More about the AWS Machine Learning service can be found
AAWS Data Pipeline is a web service to support the reliable processing and movement of data between AWS data processing and storage services as well as local data sources in set intervals. With the AWS Data Pipeline you can regularly access your data regardless of where it is stored, transform and process this in a scalable manner and transfer the results efficiently into AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB and Amazon Elastic MapReduce (EMR). The AWS Data Pipeline helps you effortlessly create complex data processing loads that are error tolerant, reproducible and highly available. You do not need to worry about securing the availability of resources nor manage dependencies between tasks, repeat tasks that were interrupted due to errors or timeouts or develop an error message system. AWS Data Pipeline also enables the movement and processing of data that was previously isolated in local data silos. More information about the AWS Data Pipeline Service can be found in the