Data & Analytics

Data analytics refers to the process of examining datasets to draw conclusions about the information they contain. Techniques enable you to take raw data and uncover patterns to extract valuable insights from it.

Techniques of data analytics may expose patterns and indicators that otherwise would be lost in the mass of information. This information can then be used to refine processes to improve a organisation or system's overall performance. In output, data analytics can do far more than point out bottlenecks. To set incentive schedules for players who keep the majority of players involved in the game, gaming companies use data analytics.

Data Backup and Recovery

Backup and recovery services are essential to the security of your company and customers’ data. Today, any application or system downtime can significantly impact productivity and revenues. As well as ensuring you get back online quickly and seamlessly, a backup solution can protect you from sensitive data loss and serious reputational damage.

Spiral offers a range of business continuity and disaster recovery solutions to ensure that in the event of a disaster or breach, you have the ability to get up and running quickly with minimal impact on your business.

Data Migrations Work

Most companies will reach a point where it is appropriate to implement new applications or migrate data to other systems, such as the implementation of new ERP and CRM solutions or the redundancy of legacy systems. A significant challenge is the consolidation of data from IT systems with widely differing source and goal structures. Weak data quality caused by duplicates, incomplete or incorrect data, or different data structures in source and target systems, all make up the project for data migration.

The scope and magnitude of the migration of data is underestimated in certain situations. At Experian, we work with clients to create the migration scenario that is most appropriate for clients needs and requirements and where the highest priority is to enhance data quality.


Apache Hadoop

This one is an open-source framework that permits for the distributed processing of huge data sets of an enterprise. It offers vast storage for all types of data, refined data processing power as well as extraordinary handling capability for virtually endless amplified tasks or jobs. Hadoop’s HDFS file system caters high-end access to application data.


Linear scalability along with verified fault-tolerance over commodity hardware or else cloud infrastructure build Apache Cassandra. This is one of the finest platforms for mission-critical data. Cassandra's cloning activity across several data centres that is the prime service. Cassandra is used by companies having large as well as heavy data sets including Twitter, Netflix, Reddit, OpenX, Cisco, CloudKick, Digg, Ooyala, and others. Cassandra enables overall Hadoop integration, in conjunction with Pig & Hive.


An organization can use this software when in need of random, real-time access for reading/writing to their Big Data. HBase is a distributed, open-source, versioned, column-orientate store designed after Google's Bigtable. Google's Bigtable is a distributed storage system used for the organized data via Chang et al. Alike Bigtable that leverages the distributed data storage offered through the Google File System, HBase has similar types of capabilities over Hadoop and HDFS.

Apache Spark

Spark amongst the rapid and accustomed engine for sizable data processing. It provides high-level APIs within Scala, Java, Python & R. Also, offers a rich set of libraries inclusive of machine learning, stream processing and graphical analytics. To stay ahead along with gaining maximum business advantage, we offer processing & analysis services in order to support Big Data applications utilizing opportunities like streaming analytics, machine learning and others.