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Big Data Analytics

The Opportunity: Business Insight Through Analysis of Large Data Sets

 

The amount of data collected by enterprises continues to grow at an incredible rate, with organizations across all sectors gathering terabytes of data from ecommerce, social media, smart devices and other online/mobile channels. Increasingly, these organizations are becoming aware of the mission-critical insight that could be hiding in these Big Data collections. Relevant analysis of this information could deliver otherwise unavailable insight into customer preferences, systems performance and much more.

 

The Challenge: Securely Providing Unified, Scoped & Monetizable Views of Data from Diverse Sources

 

The dispersed nature of today’s hybrid enterprise combined with the inherent complexity of Big Data itself means that taking advantage of this opportunity can be a considerable challenge. Performing Big Data analysis requires access to data from many disparate sources, both on-premise and distributed across multiple cloud applications. Access of this kind means dealing with a complex web of associated integration points, query formats, governance policies and access management systems.

Once the information has been aggregated, there still remains the problem of gaining meaningful insight from it. The Hadoop platform has done a great deal to make Big Data analysis possible. But to get insight they can use from this analysis, enterprises will often need to give specific departments and individuals a way to retrieve the precise scope of data they are concerned with. Furthermore, enterprises will increasingly seek ways to share data (or subsets of data) with partners, customers and other external parties and to meter the consumption of this information – often with the goal of monetization. 

This will become increasingly important as enterprises start to gather more and more data from the Internet of Things (IoT). Only if data can be shared easily, securely and in a metered fashion will the promise of IoT become a commercial reality. 

 

The Solution: Creating Data Lenses with an API Gateway

 

Layer 7’s Data Lens Solution provides everything needed to create secure, customized views of Big Data. The Data Lens Solution uses Layer 7’s API Gateway technology to:

  • Access enterprise data securely from a wide range of sources including Big Data platforms as well as enterprise databases, file systems, applications and caches
  • Use dynamic data discovery to easily configure the scope of data exposed by automatically-generated RESTful API entry points
  • Control access and quality of service by attaching authentication/authorization policies and SLAs to these entry points
  • Monetize data by metering use of these API entry points
 

The Layer 7 Value: The Industry’s Leading Gateway for Big Data Analytics

 

Layer 7 offers the industry’s leading API Gateway technology. Forrester Research has recognized Layer 7 as a Leader in the API Management and SOA Gateway spaces. Layer 7 API Gateways offer: 

  • Military-grade security certifications including FIPS and Common Criteria EAL4+
  • Unrivalled functionality for API composition, protocol translation and SOA connectivity
  • Easy integration with leading enterprise products from CA, Microsoft, IBM and Oracle

Layer 7 API Gateways have been used in multiple Big Data use cases. The API Gateway technology provides a complete Data Lens Solution, including critical features for:

  • Access to data from the full range of Big Data systems and backend sources
  • Data discovery, data scoping and automated API endpoint composition
  • Data cleansing, aggregation, filtering, tokenization, translation and encryption
  • Service level agreement (SLA) enforcement and caching
  • Access management, authentication and authorization
  • API usage analytics and metering
 

Solution Brief: Building Data Lenses Using Layer 7

 

Aggregate & Manage Access
to Data Sources

Layer 7's Data Lens solution gives the hybrid enterprise a new capacity to expose customized data views that can be monetized and accessed for mobile, analytics and Internet of Things use cases.

 

Read the Solution Brief >>