Download Reporting and Query Tools and Applications

By
N.Gopinath
AP/CSE
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There are 5 categories of Decision support
tools, They are;
Reporting
Managed Query
Executive Information Systems
OLAP
Data Mining
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Reporting tools can be divided into two types.
Production reporting tools
Desktop report writers.
Production Reporting Tools:
• It will let companies to generate regular
operational reports or support high volume
batch jobs, such as calculating and printing
paychecks.
• This tool includes third generation languages
such as COBOL, specialized fourth generation
languages and high end client/server tools.
2. Report writers:
• Inexpensive desktop tools designed for End users.
• Generally they have graphical interfaces and built in
charting functions.
• They can pull a group of data from a variety of data
sources and integrating them in a single report.
• Vendors are trying to increase the scalability of report
writers by supporting 3-tired architecture in Windows
NT and Unix server.
• At the beginning they are offered for Object oriented
interfaces for designing and manipulating reports and
modules for performing ad hoc queries and OLAP
Analysis.
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It shields end users from the complexities of SQL
and Data base structures by inserting a meta
layer between Users and the Data base.
Meta layer is the software that provides subject
oriented views of a data base and supports point
–and –click creation of SQL.
They have embraced three tiered architecture to
improve scalability
They support asynchronous Query execution
and integrate with web servers.
These vendors are racing to embed support for
OLAP and data mining features.
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An executive information system (EIS) is a
type of management information
system intended to facilitate and support the
information and decision-making needs of
senior executives by providing easy access to
both internal and external information
relevant to meeting the strategic goals of
the organization.
It is commonly considered as a specialized
form of decision support system (DSS).
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The emphasis of EIS is on graphical displays
and easy-to-use user interfaces.
They offer strong reporting and drilldown capabilities.
In general, EIS are enterprise-wide DSS that
help top-level executives analyze, compare,
and highlight trends in important variables so
that they can monitor performance and
identify opportunities and problems.
Advantages of EIS
 Easy for upper-level executives to use, extensive computer
experience is not required in operations
 Provides timely delivery of company summary information
 Information that is provided is better understood
Disadvantages of EIS
 System dependent
 Limited functionality, by design
 Information overload for some managers
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In computing, online analytical processing, or OLAP is an
approach to swiftly answer multi-dimensional analytical
(MDA) queries.
OLAP is part of the broader category of business
intelligence, which also encompasses relational
reporting and data mining.
Typical applications of OLAP include business reporting for
sales, marketing, management reporting, business process
management (BPM),budgeting and forecasting, financial
reporting and similar areas, with new applications coming
up, such as agriculture.
The term OLAP was created as a slight modification of the
traditional database term OLTP (Online Transaction
Processing).
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OLAP tools enable users to interactively analyze
multidimensional data from multiple perspectives.
OLAP consists of three basic analytical operations:
consolidation (roll-up), drill-down, and slicing and dicing.
Consolidation involves the aggregation of data that can be
accumulated and computed in one or more dimensions.
Slicing and dicing is a feature whereby users can take out
(slicing) a specific set of data of the cube and view (dicing)
the slices from different viewpoints.
Data mining tools are software components and theories
that allow users to extract information from data.
 The tools provide individuals and companies with the ability
to gather large amounts of data and use it to make
determinations about a particular user or groups of users.
 Data mining tools can be classified into one of three
categories:
1. traditional data mining tools
2. dashboards, and
3. text-mining tools.
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Help companies establish data patterns and trends by using
a number of complex algorithms and techniques.
Some of these tools are installed on the desktop to monitor
the data and highlight trends and others capture information
residing outside a database.
The majority are available in both Windows and UNIX
versions, although some specialize in one operating system
only.
While some may concentrate on one database type, most
will be able to handle any data using online analytical
processing or a similar technology.
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Installed in computers to monitor information in a database.
Dashboards reflect data changes and updates onscreen —
often in the form of a chart or table — enabling the user to
see how the business is performing.
Historical data also can be referenced, enabling the user to
see where things have changed (e.g., increase in sales from
the same period last year).
This functionality makes dashboards easy to use and
particularly appealing to managers who wish to have an
overview of the company's performance.
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Its ability to mine data from different kinds of text — for
example from Microsoft Word and Acrobat PDF documents
to simple text files.
These tools scan content and convert the selected data into
a format that is compatible with the tool's database, thus
providing users with an easy and convenient way of
accessing data without the need to open different
applications.
Scanned content can be unstructured (i.e., information is
scattered almost randomly across the document, including
e-mails, Internet pages, audio and video data) or structured
(i.e., the data's form and purpose is known, such as content
found in a database).
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