Data is a serious business advantage with both current and future. It is essentially important to store, manage and analyse data in an appropriate way. The main objective of Data Lake seeks is to overcome the challenge of enterprise-wide repository to store every type of data in the consolidated place. Also, it has to be made easily available to serve users and applications.
At any rate in its beginning, a Data Lake ought not to be viewed as a substitution to the Enterprise Data Warehouse (in the event that one as of now exists). The main role of the Data Lake ought to be to give a situation where clients can undoubtedly get to, analysis and improve with any information without the hazard or dread of affecting Business as normal or Operational exercises. The Enterprise Data Warehouse can even now assume a vital part for Operational and Business as regular reporting – and in doing as such permit the Data Lake to unreservedly work as an instrument of advancement.
Prepare, Standardize and Store ANY Type of Data in its crude configuration Irrespective of starting point, structure or organization. As all information is put away in its crude frame, clients are enabled to go past the structures typically found in information stockrooms to investigate and reveal new reports/bits of knowledge.
The information lake is the place information lives as near its regular state as could reasonably be expected – the information structures and necessities don’t should be characterized until the information is required. Ought a Data Lake not at all like Data Warehouses, to not require pre-characterized outlines.
An efficient Data Lake design seeks to decouple storage and compute so the right analytics tools can be used (and paid for on a needs basis) at the right time based on the type of analysis required.
Users should be able to get access to data they require, fast, to encourage innovation, experimentation and accelerated time to insight. Processes to access data should be well defined, clear and quick – and users should be able to choose from multiple analytical tools to support advanced analytics use cases that go beyond traditional BI.
Data lakes should be deployed in a healthy and complete technology ecosystem that enables users to turn Data from the lake into valuable insights, using multiple analytical platforms to support analysis of different data types and intelligence use cases (Streaming Data, non-relational data sets etc)
Amazon Web Services provides a varied range of professional technologies to build cost effective, accessible and high performance Data Lakes based on industry best practices. CloudCDC is an AWS Advanced partner with Big Data Competency.
CloudCDC provides Enterprise Grade professional services and customised solutions for high performance Data Lakes and analytics environments on Amazon Web Services. Our team is highly efficient and specialized in working across broader scopes of Amazon Web Services and tools to provide out of the box solutions.
Our objective is to bring fruitful results and goal achievements.
We specialize in designing, building and implementation of Analytics environments with a wide range of Amazon Web service technologies
CloudCDC provides services to design and build comprehensive analytics structure by utilizing a wide array of AWS technologies Redshift, Lambda, AWS IoT, S3, Kinesis, DynamoDB, Hadoop on EMR and RDS. Our team end to end solutions to deliver defined business results.
We are experts in helping clients with the most effective and appropriate AWS Platform services and provide the perfect combination of out of the box technologies with customization. Even coding and development is provided wherever needed to expedite the project timelines and minimize the challenges.
Contractually defined outcomes
We totally understand in delivering results with complete definition. We set genuine timelines and commit our clients to achieve what they desire. We wish to deliver success to our clients and achieve that extra milestone.”
Agility and minimal upfront investment
Experience an on-demand & cloud inspired engagement model with minimal upfront investments and a focus on rapid time to insight. Projects are divided into multiple micro stages and deliverables which gives our clients the flexibility to evaluate results and outcomes at each stage before participating further into identified solutions, technologies or platforms.
An impressive track record
CloudCDC has been in business since a while now and has one of the most experienced AWS and Redshift teams with a demonstrated track record on large enterprise deployments. We are proud of our team and deliver the best we can, everytime.