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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.

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Database Schema Discovery
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.

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The Solution
Database Schema Discovery
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.

4. info@connexica.comwww.connexica.com +44(0)1785 246777
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
Database Schema Discovery

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Database Schema Discovery
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?

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Database Schema Discovery
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?

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Database Schema Discovery
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.

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Database Schema Discovery
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.