Big Data

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Data is the most valuable currency in the idea economy, where ideas that hit the market the fastest—win. Big data done right extracts value immediately to make customers happy, inform big decisions quickly, and find the waste and risk that should be eliminated first. When big data becomes business practice, the experiment ends and the experience wins. The data-driven organization best accomplishes continuous improvement and is most capable of planning for success with predictive power. Our solutions are targeted to specific needs of the different organizations wishing to harvest data previously unreachable through traditional means. Our solutions combine industry knowledge with best-in-class implementations and delivery models.

Our Offerings:

Ability to leverage high volume, velocity and variety of data to develop new previously difficult to achieve insights into streaming and unstructured data to make informed decisions about new channels, products and customers.

Ability to query and manage high volume of data efficiency and cost effectively, while understanding how Big Data will and plays an important part in your existing DW/BI program. It will also clearly sets the steps needed toward a Big Data Analytics future for your program.

Looking for an IOT implementation provider? Look no further than EverythingD. We provide a one-stop shop on hardware, simulations, embedded testing and the Big Data capabilities you need to be successful with your implementation.

Set yourself apart with an implementation of a Big Data stack that will give you the benefit of reduced costs for storing and managing data while taking you to the next step of being able to combine various sources into actionable insights.

New technologies like NoSQL, MPP databases, and Hadoop have emerged to address Big Data challenges and to enable new types of products and services to be delivered by the business.

One of the most common ways companies are leveraging the capabilities of both systems is by integrating a NoSQL database such as MongoDB with Hadoop. The connection is easily made by existing APIs and allows analysts and data scientists to perform complex, retroactive queries for Big Data analysis and insights while maintaining the efficiency and ease-of-use of a NoSQL database.

NoSQL, MPP databases and Hadoop are complementary: NoSQL systems should be used to capture Big Data and provide operational intelligence to users, and MPP databases and Hadoop should be used to provide analytical insight for analysts and data scientists. Together, NoSQL, MPP databases and Hadoop enable businesses to capitalize on Big Data.