Data Warehousing (ETL, BI)

Data warehouses are often at the heart of the strategic reporting systems used to help manage and control the business. The function of the data warehouse is to consolidate and reconcile information from across disparate business units and IT systems, and to provide a context for reporting and analysis.

• Corporate performance management
• Profitability analysis
• Consolidated financials
• Regulatory compliance and audit

As strategic as they are, enterprise data warehousing projects are highly complex and can be risky. Projects fail almost as much as they succeed, often because of long development cycles, poor information quality and an inability to adapt quickly to changing business conditions or requirements.

Planning a warehouse that survives contact with reality

Arush Soft undertakes an extensive data analysis before the design of a data warehouse. The planning process takes into consideration data profiling and data quality — knowing what data you actually have is the natural starting point of building a successful data warehouse. Some of the other critical steps we observe are:

• Data integration and reconciliation
• Data quality and Master Data Management
• Iterative delivery instead of big-bang releases
• Packaged data warehousing applications where they fit
• Data warehouse and application performance engineering
• Deployment and change management

Business challenges — BI technologies

Arush Soft provides your company with solid support to identify and implement the best performance-management, business-intelligence and analytics technologies, so the organisational, financial and operational instruments are realised in the business. With business-intelligence techniques we transform raw data into meaningful, useful information for analysis — supporting decisions that range from operational to strategic.

Our method of information strategy, data warehousing, data mining and information analytics measures, analyses and optimises business performance across the entire enterprise. We provide, implement and support a complete BI platform, from the warehouse and extract-transform-load tooling through to tailored end-user capabilities.

The consolidation problem

• Silos, diverse data sources and data exposition — with multiple sources there is no single version of the truth.
• Time delay between an event happening and the business being able to see it.
• Risk created by manual reconciliation and undocumented spreadsheet logic.

The issue is compounded by increasing organisational complexity: proliferation of multiple systems, multiple locations, and the dynamics of mergers and acquisitions. It is not unusual to see senior executives spending time debating and resolving data issues rather than dealing with the business issues at hand.

ETL processes — compressing the decision cycle

ETL — extract, transform and load — is the set of processes by which data is extracted from numerous databases, applications and systems, transformed as appropriate, and loaded into target systems including data warehouses, data marts and analytical applications. The first part of the process is understanding the data sources. The transformations are organisation-specific, and integration is sometimes included in the ETL process because it requires in-depth knowledge of the organisation and its business.

Data modeling. While there are modeling commonalities within a vertical industry, every organisation has its own way of doing business; these unique processes should be included in the models.

Data warehouse design. Arush Soft provides data warehouse design services with consultants who understand the processing requirements and have the ability to deliver high-performance data warehouses. More than half of all development work for data warehousing projects is typically dedicated to the design and implementation of ETL processes. Poorly designed ETL is costly to maintain, change and update, so it is critical to make the right choices about the technology and tools used to build and maintain those processes.

• 60%Of effort is ETL — we plan for it
• 99.5%Load success SLA we design to
• 4–8 wksTo a first governed data mart