Data Warehousing and Business Intelligence Solutions
The Implementation Challenge
The objective in data warehousing is to build a high-performance
information repository that serves as a strategic resource. Unlike
traditional decision-support systems, the data warehouse is built on an
active model of your information needs and consists of a synthesis of key
operational and historical data as well as relevant data from outside the
organization.
Factors that are crucial to the successful implementation of a
data warehousing solution
- Proper designing and implement the databases that lie at the heart of your data warehouse. The right architecture and design can ensure performance today and scalability tomorrow.
- All components of the data warehouse solution -- data repository, network, application logic, and user interface -- must be designed to work together in a flexible, easy-to-use way.
- Develop a consistent data model and establish what and how source data will be extracted.
In addition to addressing these factors, you need the data warehouse
created quickly so that your organization can gain the business benefits
as soon as possible. A data-warehousing project can unquestionably be
complex and challenging: How do you get the appropriate solution, with the
right pieces, delivered as quickly as possible?
The Solution: Data Models and Technical Expertise
Our consultants are experts at delivering high-performance, scalable, and
reliable data warehouse solutions that achieve early results.
Our comprehensive data warehouse program combines database technologies
with the practical integration and implementation experience of our consultants.
- We have the right skills and resources to assist you in creating your data warehouse.
- Our expertise in databases, gateways, query and analysis tools, and third-party software ensures that you get top-notch technical knowledge
- Our consultants bring product know-how combined with industry and project experience to every project.
Analyze the Business Needs
Since the data warehouse is often strategic in nature, careful analysis
and planning is a critical first step. INFODATA can assist you in
- Analyzing your organization's business objectives, decision-making process, operational environment, and technical architecture to properly establish the scope of the data warehouse implementation.
- Our consultants begin with a business need analysis that identifies business and technology requirements for the data warehouse solution.
- We match these requirements with a set of models and architectures.
- We develop an overall implementation plan that encompasses the initial scope as well as longer-term objectives of the data warehouse.
Design for Performance
Your information repository must be robust and scalable enough to store,
organize, and aggregate a huge stream of information gathered from multiple
systems over long periods of time. At the same time, it must support complex
ad hoc queries. Too often, data warehousing projects are derailed because of
inaccurate database sizing or a poorly tuned database design
The best choice for the design and implementation of a high-performance
data warehouse is the same company that builds the database itself. Our
consultants are the experts on different technologies, and bring the most
advanced techniques and tools for database design and implementation. With
practical experience building and managing very large databases, our
consultants can deliver a high-performance data warehouse solution.
Create the Data Structure
Defining the data to collect and store is one of the most important steps
in ensuring that operational data is transformed and integrated into the
data warehouse. The data structure is the basis for integrating your source
systems, and it serves a broader function as an overall information map of
the enterprise. The success of your data warehouse depends to a large extent
on the accuracy, consistency, and correctness of this central integration point.
Our consultants apply a number of techniques to verify and refine your
data model. The result is a practical, accurate information map that helps
you integrate your disparate data sources into a single, coherent framework.
Plan for the Future
We deliver a scalable, high-performance application that can grow with
you as your needs change. Once the data warehouse is up and running, Our
consultants set up database management procedures, analyzes data management
performance, benchmark new configurations, and plan the next steps to expand
it. The right architecture can form the basis for a definitive,
enterprise-wide data warehouse. We will help you evolve your data
warehouse, which might include increased functionality, more users,
or additional data sources. The result is a system that encompasses all
existing environments and provides access to key decision-makers at every
level of your organization -- today and in the future
Extraction, Transformation and Loading (ETL)
ETL is the process of identifying critical data sources (both internal
and external) and their respective data for analysis and migration to a
separate database and/or data warehouse. Various tools are available to
carry out this exercise. It identifies and classifies both "good" and "bad"
data. It feeds the data migration effort and helps to ensure that only "good"
data is migrated to the new data repository. It is also very useful in
helping determine if the analysts and modelers discovered all entities and
attributes.
A simplified example of the process would be:
- Determine the scope of the project.
- Create a logical model - fully attributed.
- Determine data sources of each attribute.
- Evaluate characteristics and properties of each attribute.
- Build requirements for tools selection.
- Purchase tool.
- Test each data source for valid/invalid data.
- Document all data attributes (Meta data).
- Determine what to do with data marked "invalid."
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