Typical examples of system integration
Zap-In Technology


Zap-In delivers ultra-high-speed database processing
functions either alone or in combination with other systems.
Some typical examples of system integration utilizing the strengths of Zap-In
and its high performance and advanced functions are introduced below…

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1. Applicable to ultra-high-speed databases for use in data analysis

Zap-In may be able to complete in a few minutes processing that takes a whole day in an ordinary database system, or to complete in a few seconds processing that had taken tens of minutes. What kinds of improvements in business efficiency could result from such increases in speed?

Switching from monthly to daily reports should result in surprising progress in business analysis and management decision-making. The efficiency of analysts’ work should improve dramatically if they are able to get in several seconds analysis data for which they had to wait tens of minutes before.

System integration examples


Using Zap-In to analyze data from existing core databases

2. Big Data systems

Generally the speed of processing in a database system decreases markedly as the volume of data grows. Zap-In makes it possible to develop database systems for Big Data that had been abandoned until now due to decrease in processing speeds.

Example of system integration


Big Data processing with data collected from stores nationwide

3. Applicable to data cleansing

Data cleansing improves the quality of a database by identifying duplication, errors, and differences in expressions within the database and deleting, correcting, and normalizing them. It is essential to operation of a database system.

Zap-In delivers powerful high-speed, multifunctional database cleansing features. It is usable for both interactive data cleansing in which work proceeds quickly through an interactive approach while checking the data and steady-state, fully automated automatic cleansing.

Example of system integration

Data cleansing on migration from an old database to a new one

Data cleansing when integrating data with slight differences in formats and expressions between facilities into a head-office database


4. Applicability to data warehouses

Data warehouses are systems for organizing, storing, and using data to assist in decision-making through analysis of large volumes of past data. They need to be able to process a wide range of data types in large volumes.

Comparison of Zap-In with a standard data warehouse system

Standard data warehouse system

Hardware: Special-purpose system consisting of multiple modules (CPUs and storage)

Price: High

Performance on complex processing: Performance decreases with complex processing (e.g., referencing data among multiple modules)

Data warehouse using Zap-In

Hardware: Can use a general-purpose PC server

Price: Low (1/10 that of a data warehouse, or lower)

Performance on complex processing: Capable of high-speed processing

Example of system integration

4A data warehouse system for administration and processing of large-scale data using Zap-In and a Big Data system

5. Applicable to data analysis

Zap-In demonstrates its power in data analysis of Big Data.

While spreadsheet software makes it easy to manipulate data in spreadsheet format, it also has drawbacks including its inability to handle large-scale data and its lack of functions such as those needed to process JOIN operators. While it makes it easy to graph data as a business intelligence tool, it lacks advanced data-processing functions. Programming is required to use it to process a standard database.

Zap-In demonstrates its performance in analysis of Big Data through its functions for advanced manipulation of data in spreadsheet format, suitability to large-scale data, ultra-high-speed processing, and automated programming feature. It also can be used to distribute and graph the results of processing because it can be used together with spreadsheet software.

Example of system integration

Linkage with spreadsheet software to enable high-performance, high-speed analysis of Big Data

6. Applicable to use as a database server for a Web service

A database servicer to handle large volumes of product data is essential to e-commerce and other Web services. Its processing speed, turnaround time, and high performance are keys to a successful Web service. Response times for customers tend to lengthen with services that need to provide features such as high-performance product search functions.

Use of Zap-In as a database server for a Web service puts its ultra-high speeds and high performance to highly effective use.

Example of system integration

Using Zap-In as a database server within a Web service

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