CXMETA Overview

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One of the biggest challenges IT teams face is managing the information needs of their business users and providing them with timely answers from an ever increasing set of data sources that are spread across multiple technologies and locations.

Database Schema Discovery

The Challenge

Many 3rd party systems include pre-canned reports, often leaving business users

requiring information that is not readily available and forcing IT teams to either

speak to the supplier and pay for bespoke report writing work, or attempt to obtain

the information themselves by using a compatible report writing tool.

Even before sitting down to write the report, accessing the right data from the right

source is easier said than done. For organisations with multiple systems there is

often a lot of duplication across the different data repositories making it difficult to

know which system has the latest and most up-to-date information.

In addition, information requests are not tied to responses that can be readily

obtained from a single source. Often there is a need to join data together to provide

a consolidated data view, requiring IT teams to extract and move data from multiple

systems into a centralised repository such as a data warehouse.



Making the Right Information Available for Reporting

Before writing a new report the developer needs to understand where the data

required for the report resides. The developer then needs to understand how to join

that data together to apply the right context to the report which can be an

extremely difficult task.

Without understanding the structure of the database in terms of tables,

relationships, keys, indexes, column types etc… and how those relate to the

front-end application used to populate the database, it is not possible to produce a

report over anything other than the simplest of systems.

For system Integrators who are designing Data Warehouses or building reporting

structures such as Cubes or Universes, a key requirement is to work with a data

analyst who understands the systems and a business analyst who understands how

the captured information is used by the business.

By understanding the business requirements and the schemas containing the data, it

is possible to generate the Structured Query Language (SQL) required to pull out

information from the source system. The SQL can then be used to generate reports

or as the basis for creating de-normalised FACT based business views for use in a

reporting database or Data Warehouse.


The Solution


Wouldn’t it be great if you didn’t need to have the original author or a hard-core

systems expert to help you to understand how to get access to business data from

an otherwise unknown database?

Wouldn’t it be great if the business analyst who understands the data from an

organisational perspective and is the person asking the difficult questions about

company performance, customer retention, pipeline and cash-flow is able to get at

this information themselves with minimal or no assistance from an IT team at all?

CXMETA provides IT teams with not only a way of understanding 3rd party database

schemas, but also delivers a simple to use mechanism to build FACT based business

views in SQL for use in a reporting database or Data Warehouse.


CXMETA is a simple to use

software tool that inspects

and analyses the structure

and content of a schema

and presents back facts

that help align the logical

view of the data to the

physical structures that

make up the database.

CXMETA enables none SQL

experts to generate FACT

based SQL which can be

used as the basis for

business reporting or

establishing the key

structures within a Data

Warehouse.

Introducing CXMETA




CXMETA analyses database schema information and produces a searchable

metadata repository which can be used to identify key business domains within the

database and generate FACT based SQL without the need to understand data

modelling or SQL coding.

By pointing the tool at a database, CXMETA gathers key information about data

usage and linkages and assembles a Metadata repository that provides real insight

into how the database is constructed and what tables map to key business

domains.

How Does it Work?



The derived Metadata includes:

The tables defined within the schema

The columns defined within the schema along with their association to tables

and views

The views defined within the schema

The key constraints defined within the schema including the constraint type

and which tables and columns the constraints relates to

The indexes defined within the schema

Record counts for each table to help identify data hotspots

Key field analysis to identify uniqueness in join columns and help identify

multiplicity between tables

Using a simple Google style interface users can quickly identify the key business

domains and view this as a drillable logical data model. Each model can then be

converted into a physical SQL statement that can then be used as the basis for

multiple reports or as the basis for a FACT based SQL view.

How Does it Work?



From selecting a driving table, CXMETA

builds a schematic showing related tables

and links. This view can be expanded out to

show other relationships and table joins,

allowing you to break down the overall

database into a series of mini domains.

What Does it Look Like?

From selecting a driving table, CXMETA

builds a schematic showing related tables

and links. This view can be expanded out to

show other relationships and table joins,

allowing you to break down the overall

database into a series of mini domains.

CXMETA enables you to view primary and

foreign keys,data items, formats and links

to other tables and columns.



CXMETA automatically generates the SQL

from the domain metadata, providing you

with options to expand or reduce the scope

of the statement through a simple point

and click interface.

What Does it Look Like?

CXMETA allows you to validate the SQL

against the database and export the SQL

into the clipboard or file, save away the

domain view for later analysis, or use the

SQL to automatically generate a data

source and index definition within CXAIR.

CXMETA Overview

Technology

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