Data Warehousing | The Ironside Group

By: Ironside Group  09-12-2011
Keywords: Data Storage, Data Warehousing, data warehouse

The Requirements

It’s no secret that today Companies live on their data, and also are producing more of it than ever before. And the data is being produced by a myriad of systems, inside and outside of the organization, in a dizzying array of formats.

Data warehousing provides the foundation not only BI systems, but for many other uses as well. The data warehouse becomes the source of consistent, accurate information for the entire enterprise. It is the “go to” source for:

  • Data mining
  • Historical Records
  • Data Integration
  • Consolidation of multiple sources
  • Additional sources and external data
  • Web site traffic
  • Generated data, such as budgets, forecasts and quotas

A data warehouse is not simply an accumulation of important data It has to be managed, cataloged, validated, indexed and otherwise made suitable to become the rock-solid foundation of corporate information.

The Challenge

The challenges to developing a high performance data warehouse are considerable, and range from the very technical (such as storage architecture) to the business oriented (such as the definition of key terms).

Just some of the questions which will arise are:

  • Choice of storage platforms. Typical RDBMS or DW specialized system?
  • How to manage data Independence from originating systems, and location?
  • Storage of foundation data vs query data?
  • Response times: What is adequate, and how to provide this?
  • What is the expected mix of workloads between shorter tactical queries and the longer strategic queries, and how best to manage this?
  • Normalized or denormalized database structures?
  • Where do cubes or federated data models play a role?
  • What ETL tools and methods should we use?
  • How best to manage the flow of data, along with cleansing and validation?
  • What summary tables are needed?
  • What is the difference between a data warehouse, a datamart, and an operational data strore? How do I know which one(s) I need?
  • How can we keep the data flowing, while keeping manual intervention and maintenance to a minimum?
  • How will we know the data is correct?

The Solution

While the design issues around data warehouses are complex, they don’t need to be overwhelming. Our approach is to begin with the business requirements (current and future), and let business value drive the technical design decisions.

In today’s business environment, few if any companies can consider a three to five year investment in a “big bang” comprehensive data warehouse development cycle. Ironside Group will work with you to develop thirty to sixty day cycles, showing business value at each step of the way.

Furthermore, Ironside Group can deliver a data warehouse optimized for BI consumption. This can be the solid foundation on which to build your BI initiative, and all other data intensive initiatives for years to come.

To build the foundation on which all further analysis is based, it’s vital the data is complete, validated, and structured for proper access by the the BI tools. In addition, the appropriate ETL, data cleansing and meta-data tools and processes need to be identified.

Ironside Group provides you with the end-to-end view of your information flow, from gathering and cleansing, all the way to the boardroom.

Our experienced consultants and data experts can provide you with services such as:

  • Data extraction expertise
  • Technical and architecture Design
  • Database and data tool assessment
  • Database Design
  • Meta data services (management and coordination, documentation, MDM (Master Data Management), etc.)
  • Data Cleansing
  • Considerations for “Non Traditional” data storage options, such as cube, in-memory database, column oriented database, and other high-performance techologies and techniques
  • Data storage suitability assessment
  • Data Readiness assessment for Business Intelligence
  • Data and Process Optimization
  • Project Management

Keywords: Data Storage, data warehouse, Data Warehousing

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