Sybase operational BI execution manual (1)

Bkjia.com comprehensive report tips and tips: how to deploy operational business intelligence solutions for your Enterprise

Preface
Chapter 2: transforming data explosion into business intelligence
Chapter 2: Operational BI-opportunities for reflection
Chapter 2: benefits-establish BI cases in sequence
Chapter 2: solid foundation-platform strategy
Chapter 2: surpassing data warehouse-new data Solution
Chapter 2: deployment time: managing the initiator, complexity, and expected value
Chapter 2 cost factors: Finding value in all appropriate fields
Chapter 2: Bottom line: the commercial value of BI is faster, more flexible, and simpler.

Preface

This operational BI manual outlines the main considerations for companies that want to transform data explosion into business intelligence. This manual is compiled by Sybase to provide guidance for managing upgrades from traditional data warehouses to dynamic analysis engines. This dynamic analysis engine can convert data into valuable business intelligence while operating businesses.

Why Sybase?

Underlying technologies and platforms must be able to support and optimize operational BI business requirements. Integrate Sybase®With the advantages of IQ analysis platform and related business intelligence software and hardware, enterprises can choose solutions tailored for operational BI. In this manual, Sybase provides guidance to enterprises not only through technical means, but also by considering the overall business from initial evaluation to ROI evaluation. We hope this will help you.

Chapter 2: transforming data explosion into business intelligence

In today's world, the survival of an enterprise depends on its ability to analyze data and make clear and informed decisions accordingly. However, as the amount of data collected by enterprises increases exponentially every year, many enterprises find it difficult to achieve their long-term goals.

In fact, the ever-changing business needs that drive the company forward will only generate more and more data. The increasing demand for rules forces enterprises to store and maintain rapidly growing data. At the same time, enterprises try to collect data throughout the company in order to obtain the most complete analysis data.

The result is that a large amount of data flowing into the enterprise system may cause the existing analysis process to crash, while a large amount of data is converted into more complex queries that require longer processing. There is no doubt that this result has resulted in loss of IT staff and system performance, but the impact on enterprise operations is the real loss, knowledge workers need to wait longer for key query results.

The shortcomings of traditional analysis tools aggravate the problem. These cumbersome tools are created to analyze transactional data stored in the data warehouse, but they cannot cope with the current data explosion. In the end, the enterprise either cannot process the query, resulting in reduced information or splitting the query into several smaller processes, resulting in a longer processing time.

With the shortening of the decision-making cycle, many enterprises cannot wait for slow analysis results. Financial service enterprises need to complete risk analysis of online transactions within several minutes, rather than a few days. Retail Enterprises need to customize promotion plans based on customer data within several seconds, rather than just a few hours. Disappointing: enterprises only know that time is money, but do not have a business intelligence function that can quickly and accurately analyze complex data.

Real-time release Decision-Making

For many companies, the answer to the question is to convert business intelligence from a "distant parent" business to a business that is directly integrated into the first-line process. This strategy is called operational business intelligence (BI ).

According to Forrester Research, the use of business intelligence has been transformed into the process of incorporating BI into daily decision-making at the business operation layer. 1. Many existing BI implementation solutions aim at high-end policy problems that can tolerate certain latencies. However, operating BI users want and want real-time responses. This shift to the operational level leads to different analysis requirements from traditional BI. For example, call center administrators may use strategic BI for planning and prediction, while call center representatives use operational BI to respond to complex customer queries in real time.

The operational BI depends closely on the Real-Time query of the target, which is used to provide detailed information. Call Center representatives may use real-time integrated control panels from various non-integrated data sources to create a single view of customers. In this case, fast data access is very important. In many cases, operating BI users are front-line employees. They cannot wait for data preparation and loading, nor wait for a long time for query results. What they need is instant information. In fact, operational BI features a rapid increase in the number of users and query complexity, as more and more employees regard operational BI as part of their daily business processes. These users need to respond quickly regardless of the source data. In many cases, they need to use BI tools to collect data from multiple data sources in real time.

Such data sources are not limited to traditional data storage devices, especially whenCompliance ReportMore and more pressure, especially in the case. However, enterprises need to ensure that the operational BI source data stream contains valuable unstructured data. Bottom line of operational BI: to make operational BI work normally, no matter where the user is on the enterprise information flow, they must be able to collect data from multiple data sources and perform real-time response.

Solutions and technologies

Driving the rapid increase in operational BI business needs will also drive similar technological changes. To succeed in this innovative business strategy, the underlying technology and platform must support and optimize operational BI business needs. In view of this, Sybase has launched an outstanding technical solution tailored to the operational BI project. Integrates the advantages of Sybase IQ analysis platform and related software and hardware. This solution can meet the needs of operational BI at multiple levels.

◆Quick decision-making. This solution is designed for fast business query of massive data and can be efficiently processed and expanded. Users can obtain responses more quickly and load larger data volumes to make more informed business decisions.
◆Analysis Platform created for operational BI. Sybase IQ provides a powerful analysis platform specifically designed to analyze and process business queries from heterogeneous data sources that require rapid response. It is the best choice for operational BI projects and can perform query and analysis more quickly than traditional analysis solutions.
◆High Cost Effectiveness. Sybase IQ eliminates traditional-and expensive-RDBMS bottlenecks and tuning requirements. It increases and modifies database and server configurations, and saves storage space for data compression, which reduces the required cost while providing better business information.

1 Forrester: the advent of Process-Centric BI in December 2004) (Process Centric BI Emerges (December 2004 ))

In many cases, operating BI users are front-line employees. They cannot wait for data preparation and loading, nor wait for a long time for query results. They need real-time information.