Large data solutions for small budgets

Large data may indeed have great potential, but on the other hand it is also expensive. Last summer, New Vantage's partners surveyed more than 50 top executives and Fortune 1000 companies and large federal agencies. The survey found that 50% of companies have spent about $1 million trillion to $10 billion trillion in big data technology this year, while 25% have spent 10 billion dollars or more on this.

While alternatives to open source, such as Apache Hadoop, are easier to understand, they still need businesses looking for qualified people to operate. The lack of qualified personnel in relevant data, such as scientists, data architects, and so on, not only increased budgetary considerations, but also increased the barriers to large-scale popularization of large data solutions.

The McKinsey Global Research report warns that by 2018 we will lack 140000 to 190,000 employees with sufficient analytical skills, as well as a shortage of 1.5 million managers and analysts who can make informed business decisions using data-capital models.

Further complicating the situation is the seamless expansion of a considerable number of large data services, which may require more computer systems and data warehouses to be set up, which is back to the relevant budget and staff shortages cycle.

SiSense is a large data and business intelligence company headquartered in the Redwood Coast of California. The company hopes to provide large data Analysis Services for businesses of all sizes. The company wrote on its website: "Although clusters are huge, scaling of resources across a single compute node is also important." ”

At a recent strata + Hadoop World Summit in New York, SiSense launched its prism, a software that can handle a large amount of analytical work on a single machine. The company describes the software as a large data analysis tool that requires neither high-end skills nor a large budget for traditional analysis.

Let's call it a veritable mass of data socialism. SiSense's off-the-shelf software mounts 8 GB of memory by processing trillions of bits of information on the Dell Vostro 3560. Can be used on laptops for less than 750 dollars, and the software is designed to run on most inventory models.

Prism avoids the traditional requirement of large data, and offers early technology to companies with limited technology and financing constraints. It features automatic extraction of all the mainstream databases (Oracle, Microsoft SQL Server, MyServer, etc.) that can store and analyze billions of rows of data, neatly visualize data analysis, and completely cut off any script needed to sort.

SiSense's chief executive, Amit Bendov, said in a press release that Prism broke the competitive environmental level of big data.

What do you think? As more and more sisense companies offer low-cost, large data solutions, the growth of large data can even exceed expectations.

(Responsible editor: The good of the Legacy)