Turbo Data Laboratories: A Revolutionary Pursuit of Solving Big Data
The big data revolution has significantly transformed the dynamics of world businesses. Every organization today wants a taste of big data and the competitive edge it can offer through business intelligence (BI) and predictive insights which determine the prospects of a business’s trajectory. However, the underlying issue is not technology inadequacy but the massive volumes of data that need to be segregated and analyzed in a given time. At the end of the day, the efficiency factor amounts down to the data processing speed; a unique proposition that most organizations strive to achieve. This is where Turbo Data Laboratories excels as an enabler through its groundbreaking innovations in database technology of component analysis that allows the firm to develop and deliver world-class ultra-high-speed database systems. The company has developed its proprietary patented technology namely ZAP In and ZAP Over as an answer for the complexities related to big data processing speed, development of system integration, performance, function implementation and the usage of big data over the internet.
ZAP-In, with data structures and processing algorithms of in-memory databases enhances the speed of relational databases. The discreet component system of the big data processing causes significant impedances within multiple layers resulting in the reduction of the processing speed. In this traditional approach, the big data from the source is stored and managed as D5T or D5D files in data warehouses (DW) which later go undergo extraction, transformation, and loading (ETL) to extract necessary data from DW. This data then undergoes batch o simulation processes that are carried out with the help of specific programs. The results obtained are sent down for further analytics and BI which is delivered as the output for the reporting tools or Web publishers.
The company has developed its proprietary patented technology namely ZAP In and ZAP Over as an answer for the complexities related to big data processing speed, development of system integration, performance, function implementation and the usage of big data over the internet
However, Zap-In’s one stop system effectively reduces these impedances at each layer as there is no memory or storage necessary for indexes and near zero data moving impedance between functions, tools, and DW. The spreadsheets like operations enable seamless one stop processing of big data. Shinji Furusho, President, Turbo Data Laboratories, says, “Incorporating our ZAP-In database into their system in the year of 2002, Fujitsu procurement system achieved massive success in reducing their procurement cost to USD $2.8 billion from a total of about USD $30.0 billion.”
In order to make it feasible to use big data over the Internet, Turbo Data Laboratories introduced ZAP-Over Technology. The big data is too huge to be moved from one site to another, and it is considerably difficult to access that amount of data at regular internet transmission speeds. The ZAP-Over database brings together the data provided by a variety of services on a single screen of the client terminal for display. In addition, functions from multiple services are combined on the client terminal to provide them as a new service. big data owners convert the source data into a read only D5A file and put it within a Network Attached Storage (NAS) attached to the internet. This NAS acts as the server for the big data allowing users across the network to access the D5A file from any location through a virtual union table of these files on their screens. This approach has attributed heavily to the cost reduction factor while facilitating operational and data flexibility.
Turbo Data Laboratories with the help of its unique products and solutions has established a firm stature in the big data and the BI vertical. A multitude of companies in the region have adopted Turbo Data Laboratories’ technology, and in the next few years, the company intends to continue with more innovative developments to deliver to a wider spectrum of enterprises in coming days.