BIG DATA CONSULTING SERVICES
Build Big Data Solutions with Innovecs
Big data consulting services can be an enormous benefit to your big data strategy, or they can be used to build a roadmap to update your solution. Analyze and visualize data, discover patterns, propose analytical models, make informed decisions, enhance analytics, and minimize risks.
Automate merging of third-party data with your existing database
Build architecture solutions capable of processing massive data spikes
Split your data storage into two parts, historical and operational
DATA LAKE DEVELOPMENT
Benefit from a scalable and centralized repository for data storage
Make informed decisions with the help of structured and visualized data
THE GENERAL VISION OF BIG DATA SOLUTIONS AND HIGHLOAD
Big data consulting services in regards to highload can offer suggestions on how to speed up the system reaction and enhance capabilities of serving massive user spikes. Big data solution providers recommend architecture solutions that allow managing the speed of data processing regardless of data volume.
For systems where data volume grows exponentially, data auditing and verification become impossible without a well-designed solution.
Such a solution will allow cleaning and aggregating data coming from different sources, splitting it into historical and operational for better data management, and organization of a repository to boost data searchability.
Big data consulting services advice on all these topics to make data structured, identified, traceable, and rule obeyed.
Visualization, as well as reporting on the actual data, allows for creating easy-to-use dashboards and analytical tools that help companies make informed solutions.
Data modeling provides enterprises with predictions built on top of a company’s historical data. Moreover, if it is used with machine learning technology, this match generates more opportunities for effective data adoption.
LOOKING FOR A PARTNER IN BUILDING A BIG DATA SOLUTION?
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Why Entrust Big Data Consulting Services to Innovecs?
Approach to Big Data Development
Innovecs begins highload projects with a Discovery stage. A client provides Innovecs’ team with its goal and current vision. Then Innovecs provides a technical audit of data-heavy business processes and their management.
Based on this research, Innovecs begins big data consulting services. We dot our vision of the digital transformation journey and present a sustainable and easy-to-expand architecture with easy access to operating data.
Lastly, we provide application development for big data, to deliver an effective ready-to-use solution that meets our client’s requirements.
Proven Track Record in Big Data Outsourcing
Innovecs is vastly experienced in big data consulting services. We have worked with companies of different sizes, from startups to enterprises.
Innovecs has delivered projects focusing on database optimization, data migration, deployment of cluster monitoring, balancing between data segmentation, archiving, and storage subject to speed requirements. Some projects included the adoption of machine learning technology on top of big data.
Also, we help companies to choose a solution based on either cloud or physical servers. The right choice will result in optimal software performance as well as the proper management of resources and costs.
Post-release Support of the Big Data Solution
After releasing the project, Innovecs helps monitor whether data processing lives up to the client’s expectations. We help build the system of analytics with visualized dashboards to be alerted immediately when an issue arises.
Post-release support refers to the Drive stage and helps companies in their growth. In other words, correctly established analytics allows for growth points identification. For instance, if thousands of users work with one platform, optimization of one operation by even 0.1s can contribute the system effectiveness considerably.
As a big data application development company, Innovecs will help with the matching and mapping of data coming from different sources into one well-structured data set.