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The Silicon Review Asia

Percipient: Making Digital Transformation- Real, Affordable & Easy

The Silicon Review
July, 2017

thesiliconreview-percipient-2017“Our flagship product UniConnect is built to deliver connectivity, regardless of source, type or volume, at ultra-high speed.”

Percipient is a data technology company based in Singapore, founded in 2014 by four financial services professionals. Their teams are based in Singapore, India and USA. Percipient recently announced a seed fund round, led by several highly respected corporate IT heads.

Established with a mission is to help organizations reduce the complexity of their data architecture. Their flagship product, UNICONNECT, was built to hyper-accelerate connectivity between data sources that currently don't talk to each other or cost too much to integrate. These can be data sources that are legacy and modern, or structured and unstructured, real time or batch. Data from IoTs, blockchain and APIs can be easily, speedily, safely and cheaply managed using UniConnect, all without the need to make yet another copy of the data.

Percipient enables organizations to put data at the heart of all their decisions and drive scalable, efficient and cost ­effective growth by taking advantage of big data technologies and advanced analytics. The company partner with clients to design, implement and support their digital journey.

Knowing the Executive

Ravi Shankar Nair, CTO

Ravi’s prowess with big data platforms and his passion in applying technology to solve complex data challenges has earned him the tag, “Hadoopean”.

Based in the U.S., Ravi packs about 20 years of technology experience. Prior to Percipient, Ravi was responsible for Citi’s business intelligence deliverables for North America and LATAM, and for data modelling deliverables for Citi Consumer, USA.

He was previously engaged by Crimson Logic to help the company develop sustainable e-government solutions. His team developed Transwork, a critical application for ETL and an advanced mathematical expression analyzer used for rule based transformation.

Ravi is an active big data and Spark blogger, speaks at international data conferences and webinar presentations, and runs a local Hadoop user group. Over the course of his career, he has presented to over 8,000 data enthusiasts.

Ravi and his wife live with their young son in Jacksonville, Florida.

Solutions Offered

SparkPLUS

A More Efficient Spark

SparkPLUS is aimed at improving the efficiency of Spark, one of the fastest growing big data open source analytic tools currently available. While Spark provides a host of analytic capabilities within a single ecosystem, its memory-heavy design means memory outages are all too common.

By integrating Spark with UniConnect, SparkPLUS offers analysts an elegant way to lift Spark’s capabilities. This integration enables only the unified data needed for analytics to be pulled into Spark, thereby vastly multiplying  its computing space.

ScalETL

Scaled Out Transformations

Like other ETL (Extract, Transform, Load) solutions, ScalETL automates the flow of data from a source to a target database, having converted the data into the required state.

However, unlike other ETL tools, ScalETL’s integration with UniConnect means it connects to more than 50 connectors, is highly configurable, and tracks end-to-end dataflow via a single web-based user interface. This is possible with maximum scalability and performance through the use of clustering technology.

Unified API XS

APIs Joined In Memory

Application Program Interfaces (APIs) are enabling organizations to easily open their data to, and access data from, a range of external parties. For example, developers can use the GoogleMaps API to embed Google maps on webpages, and YouTube APIs to integrate YouTube videos.

However, to derive maximum value, it is often necessary to combine the data across multiple APIs. It may also be useful to combine data sourced from an API (e.g. Google Maps) with real time data (e.g. a customer’s location), and pre-stored data (e.g. a customer’s buying patterns). The Unified API XS solution helps organisations to establish a single view of this multi-sourced data in memory, thereby super-charging processing speeds and reducing security risks. This solution can be further scaled by deploying advanced processors.

Products Offered

UniConnect

Leverage ALL your data

Achieve Hyper-accelerated Connectivity

Going digital means integrating customer, risk and transaction data, often from end-of-life systems. This can be a complex task, made even more challenging by the need to access data that is multi-jurisdictional, cross-functional, heterogeneous or compressed.

UniConnect is built to deliver connectivity, regardless of source, type or volume, at ultra-high speed.

Business Intel at Your Fingertips

UniConnect lets you query data from all sources and feeds, through a single SQL interface. If you are using SAS, Spark, R, that’s not a problem either. Uniconnect is integrated with the latest data query engines to improve their efficiency, while ensuring that internal enterprise processes remain intact.

UniConnect means data is processed more efficiently, and more data is ready for use, without new skills or tools.

Big data minus the big costs

The data that traditional enterprises seek to manage today is miniscule compared to the data that full-scale digitization will bring.  UniConnect’s parallel processing technology offers more digital capability, at a fraction of the cost of traditional monolithic servers.

UniConnect supports digitization by helping enterprises to benefit, rather than be penalized, for their data growth.

UniConnect can be used to:

1) Integrate multiple data feeds and information sources for report production.

2) Provide data analysts with SQL access to an enterprise's disparate databases and real time transaction data

3) Seamlessly connect data from a traditional Enterprise Data Warehouse with a modern Hadoop (big data) platform

Our clients are able to unlock new value through easy, fast and efficient management of all data, big or small.”

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