Six top big data solutions

By:
Natalie Bannerman
Published on:

Natalie Bannerman takes a look at some of the biggest big data solutions and open source frameworks on the market for users in the telecoms industry

The ability to aggregate, process and then act on big data is no longer not an option for big businesses. By ignoring this opportunity, companies fail to monetise and gain invaluable insights not only into customers but into operations. Many companies in the telco sector are becoming more and more aware of this need and in response are creating innovative solutions to meet this demand. The solutions must be easy to use, agile and robust in order to create value.

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As waves of big data continue to swell on networks worldwide, Adtran is helping carriers to harness the power of data to build adaptable networks capable of supporting demand for the user-driven, personalisation, and self-service models of the future. Through Adtran’s SD-Access open and programmable architecture, carriers have the flexibility to scale networks and services for agile service delivery based on end users needs at work, home, and play.  To optimise network capability and to increase service velocity, Adtran’s SD-Access solution enables data-driven insights and automation using artificial intelligence (AI).  With data and AI, carrier networks have the ability to learn subscriber demands and use its intelligence to maximise subscriber’s quality of experience.

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Huawei FusionInsight is an intelligence platform that allows customers to transfer all of the big data into critical business insights actionable in real time. It features two main engines, one for massive data processing and the other for real-time data processing. The offering is agile, having an open architecture and APIs that support batch processing, micro-batch processing and real-time processing. Businesses can gain better insight into user behaviours, accelerating business decisions and opportunity. It has also been built to be as user friendly as possible. 

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Netcracker’s big data solution comprises of three components. The first is its Advance Analytics Platform, which uses a modular architecture, unique methodologies to acquire, cleanse and aggregate critical data, comprehensive analytics tools and innovative data distribution capabilities. It also has built in communications-specific scenarios and algorithms. In essence, this offers customers the ability to configure algorithms to improve sales and marketing performance and customer experience management as well as service and infrastructure optimisation. Netcracker data scientists work with operators to turn qualitative data into useful insights.

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Nokia’s Cognitive Analytics suite operates an intelligent and self-learning piece of software that uses machine and deep learning to complete its goals. It can be used as a standalone solution or be combined with other products to enable autonomous actions and real-time decisions. The suite includes several specific products; one is for customer insights, using experience data. Another uses deep subscriber and network insight,. One for fixed networks allows operators to troubleshoot network issues. One for marketing insight provides predictive analytics for subscriber behaviour. 

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Oracle’s Big Data Discovery Cloud platform is a product that allows any business to easily transform its raw data into business insights, all without the need to learn complicated tools or relying on highly specialised tools. The platform uses Oracle Big Data Cloud Service and Apache Spark to turn raw data into visual business insight in minutes. Features include the ability to find relevant data fast using a rich interactive catalogue of the data in Hadoop, the ability to filter through thousands of data sets using familiar search and guided navigation as well as the ability to load new data through self-service wizards.


Wipro 127x126Built on IBM Bluemix, Wipro has developed its big data analytics-as-a-service platform, the Data Discovery Platform. The offering speeds up insight-driven decision making through the use of industry specific prebuilt applications. Sectors include banking and financial service, education, IT, energy, marketing, manufacturing, mining and retail.

In addition the product is available on a pay-per-insight cloud delivery model. This modular approach, coupled with machine learning, natural language processing, visualisation and stream computing capability enable flexible and scalable responses. []