Volume
Five quintillion bytes of data are created every day around the world — that’s a million trillion bytes or 1 x 1018. The sheer volume of data demands specialized processing techniques in order to yield actionable insights.
The amount of customer and operational data generated by businesses grows by the day, but few companies know how to harness it to improve operations and profits.
Sophisticated analytics open the door to a whole new world of possibilities, fueling faster and better forecasting and planning, with the end result of better market performance.
Here are just a few key features of big data that companies need to keep in mind:
Five quintillion bytes of data are created every day around the world — that’s a million trillion bytes or 1 x 1018. The sheer volume of data demands specialized processing techniques in order to yield actionable insights.
Big data analytics can be produced through batch processing, or via real-time (seconds) or near real-time (minutes) processing. The faster big data analysis is generated, the more robust the processing approach needs to be.
When you have more sources of data, they’re more likely to be in different formats, including traditional documents and databases, semi-structured and unstructured data from social media, and data from IoT devices and GPS.
Backed by our cutting-edge big data services, you can make the most of advanced big data analytics in order to fine-tune your offerings, create new sources of revenue, and grow sustainably.
It’s commonly thought that big data services are cost-prohibitive for smaller businesses. While it’s true that processing, storing, and analyzing big data all require resources, those costs can be estimated with a preliminary infrastructure analysis and then mitigated by optimizing processing pipelines.
Incorrect algorithms. Unreliable data processing. Misguided conversion of insights. These are just some of the many factors that can affect the performance of big data solutions. We craft custom plans that start with choosing a proven tech stack and assessing a solution’s feasibility so your project is free from performance issues.
To ensure data’s reliability, our domain experts take an iterative approach to data cleansing, analysis, visualization, and review.
Whether you need to secure signed NDAs, design a data encryption strategy, or stay aligned with internal and external security policies and requirements, we rely on security best practices to protect your data’s integrity.
AI and big data pair well together since AI-powered apps can leverage vast amounts of data to constantly and autonomously update themselves. Our big data experts review early requirements and provide technical feedback to ensure AI and big data work efficiently, hand in hand.
contact us
.
contact us
.
contact us
.