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Lindsey Patterson

5 Big Data Companies and How They Stay Competitive

4 min read

Big data has been maturing and expanding rapidly in the recent past, with small and big companies embracing the idea of gaining insights from the massive data floating around them. Although big data has faced few challenges such as the integration with other technologies like machine learning, it has not stopped growing and being adopted in most companies. Gartner predicts that by 2018 about 50% of business ethics violation cases will be related to data.

 

There is a new trend of big data companies expanding beyond their traditional Hadoop cluster towards other platforms. A recent white paper from Tableau suggests that some of these platforms are "data-and source-agnostic." Here are five big data companies and how they have caught on with the "everything-as-a-service" trend in order to stay competitive:

 

1) New Relic

 

This is a big data company that applies a SaaS model in monitoring mobile apps and Webs that run on the cloud, premises or on a hybrid in real-time. It engages with several other technology companies in getting various plugins for its dashboard. It uses plugins such as PaaS/cloud services, database, and queuing on its monitoring dashboard from technology partners. It has an Insights software that works across the whole product line for analysis. New Relic also offers another product called Insights Data Explorer that enables users on a software to explore Insights events.

 

2) ShareThis

 

Although most people may argue that ShareThis has been around for ten years but doesn't have the green button for allowing users to share to other networks, it has a lot of data. The terabytes of data processed by ShareThis can be used by businesses in generating actionable insights. The Real-Time Marketing (RTM) Engine from the company is also great for enabling businesses to target people or prospects based on their recent, relevant interests.

 

3) SQream

 

The speed and scalability associated with this big data company make it a big player in the industry. The company uses parallel computing and GPU-based technology in offering speedy analysis of the petabyte scale. The company claims to offer speedy analysis that is up to 100 times what other big data companies can provide. The innovations promote efficiency for huge datasets, and hence reducing downtime in cloud platforms and other operations that experience heavy data processing.

 

4) Tableau

 

The company originated from Stanford University as a project that was initially designed for offering visualization techniques, analyzing relational databases, analyzing data cubes. However, it has expanded to include big data research. Tableau as the capacity to offer visualization from any source like Excel files unlike some visualization products in the technology market that can only offer visualization from certain sources. Another feature that makes it a competitive product is the fact that it can work on various devices such as PC and iPhone.

 

5) Teradata

 

The company has various big data applications such as Teradata QueryGrid, Teradata Unity, and Teradata Viewpoint that it refers to a Unified Data Architecture. The big data apps from Teradata have the capacity to offer reliable data fabric across various analytic engines. The architecture has another application called Teradata Listener that is popular with organizations that are used to processing heavy data. Teradata Unity is designed for managing data flow throughout the process, while Teradata Viewpoint is a custom dashboard of analytic tools that are designed for managing the entire Teradata environment.

 

Regardless of the data size, type, or source, any company that intends to be at par with the competition needs to invest in big data. Advancements in technology have compelled reputable big data companies to design big data products suitable and affordable to small businesses that have been previously shying away from investing in big data.