Unlock the Value in Unstructured Data
The good news is that organizations these days are storing a lot of data from connected devices, apps, transactions, and other sources – video, audio, text, and images.
The bad news is that most of this data is probably sitting untouched in multiple siloed repositories, significantly limiting business’ ability to make data-based decisions. With little or no view into key insights like market trends, customer needs/behavior, business operations, and risks, they are at a competitive disadvantage against competitors who have upped their data game.
Big data solutions help you overcome these limitations, bringing cutting edge capabilities within reach to build new competitive advantages and innovations.
As one of the leading data and analytics consulting firms, Trianz specializes helping companies turn data into decisions by identifying hidden patterns, new correlations and uncovering market trends.
How We Work to Bring Big Data to You
We have an eight-step process extending across five phases to extract real-time insights from the raw information – that flows through organizations every day.
Copyright © 2022 Trianz
Big Data Analytics Process
Copyright © 2022 Trianz
Our big data analytics consulting experts and data scientists use proven frameworks, technologies, tools, and processes to transform your organization into a data-driven enterprise.
From Discovery to Advanced Analytics and Data Science
Assessment and roadmap in big data strategy development
Design and execute proofs of concept (POCs) with Big Data Analytics labs
Support product evaluation and decision making
Production and management of pilots
Master the ‘Three Vs’ for the Full Value of Big Data: Volume, Velocity, Variety
System design by Big Data architects
Installation and configuration of Cloudera, Hortonworks, and other Hadoop distributions
Data processing using Hive, Sqoop, Pig, and Spark
Development using Java, Python, and Scala
Integration with Amazon Web Services (AWS) and Microsoft Azure Cloud environments
NoSQL processing with MongoDB, HBase
Relational analysis with Redshift, Vertica, Teradata
Analytics with Spark, R, Python
Visualization and analysis with Tableau, Datameer, Qlikview, and others
