To realize the value of data, you need a complete end-to-end solution that can manage both structured and unstructured data with security, consistency and credibility. Our Big Data Analytic suit enables convenient, on-demand access to your pool of organizational data resources that can be conveniently made available and released with minimal management effort or engineering intervention. CodeSizzler enable you to avoid chaos over provisioning data across different systems, manually merging with other system and improve on operational excellence by finding the right data at right place in right time.

We believe it is particularly important to fully understand how you use your data today and what you do today can be best enhanced by using the big data analytic tools and frameworks at our disposal.

CodeSizzler’s Approach

We execute big data projects using the following steps

We identify and understand each data source such as CRM, ERP systems or any other data sources, which needs to be “mashed up” .In this phase we interact with you to identify the current system in place and questions which it can answer. During these meetings we understand customer’s business and identify what other outcomes could be important for the business.

We complete ingest by delivering cost estimation of the proposed project based on the information provided together with mock ups based on the findings and feedback from the business.

To determine the right design for the virtual datacenter, started with an extensive discovery session to define the scope of work, goals and dependencies. The project delivery was then aligned to three key follow-ups:

Codesizzler held a significant review of the existing infrastructure to assess use cases, dependencies, applications, and files against the target platform. This culminated in a high-level design of the new Azure environment.

Prepare process is typically 100% engineering focus where we study data sources to mash up and establish key relationships between different systems to bring data to data warehouse. During this process we discover a couple of data points, which can add value for the business.

Outcome of this phase results in Building the foundation of this system that is popularly known as Data Warehouse and systems gets ready to intake the data from different systems.

We extract data from existing data sources, transform into the designed data warehouse format, and load in to data warehouse. Automated jobs are created which sends data from the existing systems to newly designed Data warehouse. During this process engineers from both teams interact to deliver the business output promised at ingest Step. We ensure engineers actively participate in the process of building visualization dashboards to simply support for future.

Serve is typically the final phase of project where the production system is delivered to the customer and is open to get feedbacks in terms of KPI addition or bugs. The system engineering is complete and handed over to its intended business owners, end consumers and support & administration staff for day-to-day management and support.

Project Management Methodology
In all these 4 Steps, execution in the right order is extremely important to deliver successful outcome. We believe interacting in a transparent way to make sure the project is delivered in time, effective and with quality.

Codesizzler offers the completely managed system. We effectively become your IT administration and operation arms and take care of everything associated with the company’s Big Data system. We manage all servers, services, networking, security, upgrades and maintenance transparently.

Codesizzler will build additional tools, if required; to manage and maintain your unique infrastructure. Our team of software engineers and cloud specialists will pull your network, optimize your servers and recommend new architectural improvements to better leverage the cloud.