The Enterprise environment is volatile facing multiple challenges from the Data perspective including the following key ones:
- Silos, Diverse data sources, Data Explosition
- Due to multiple sources, there is no single version of the facts
- Time delay
The issue is further compounded by the increasing complexity in the organization due to proliferation of multiple systems, locations, dynamics of mergers and acquisitions, etc. It is not unusual to see Senior Executives spending time in debating and resolving the data issue rather than dealing with business issues at hand.
SQIAR can help
SQIAR works with various technology stacks that make most sense for you depending on your business infrastructure and in-house skills for supporting solutions. SQIAR implements an extensive range of BI technologies including:
- Microsoft SQL Server Analysis Services(SSAS)
- Microsoft SSIS
- Microsoft SQL Server Reporting Services(SSRS)
Following are the key elements of our services:
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, but not limited to, data warehouses, data marts, analytical applications, etc. The first part of the extract, transform and load (ETL) process is understanding the data sources. The transformations are organization-specific and Integration is sometimes included in the ETL process; because it requires an in-depth knowledge of the organization and its business.
Data Modeling: While there are modeling commonalities within a vertical industry, every organization has its own way of doing business; these unique processes should be included in the models
Datawarehouse Design: SQIAR provides datawarehouse design services with consultants that understand the processing requirements and have the ability to deliver high performance data warehouses.
Data warehouse is the foremost repository for the data available to develop an efficient and robust business intelligence architecture and decision support system. At Sqiar we strive hard to provide you with best of the breed system architecture and technology to facilitate important stretegic decisions.
Over half of all development work for data warehousing projects is typically dedicated to the design and implementation of ETL processes. Poorly designed ETL processes are costly to maintain, change and update, so it is critical it is to make the right choices in terms of the right technology and tools that will be used for developing and maintaining the ETL processes.
Some of the numerous technological approaches and solutions available on the market include:
- Traditional engine-based ETL products
- RDBMS proprietary solutions
- Third-generation ELT solutions, based on a code-generation approach that uses the power of the RDBMS engines to perform the data transformations
Some of the key technologies used by SQIAR for ETL are:
- Microsoft DTS
- Microsoft SSIS
- BizTalk Server
Data Warehouse- Single Version of the Facts:
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 provide a context for reporting on and analyzing:
- Corporate performance management
- Consolidated financials
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.
At SQIAR we undertake extensive Data analysis before designing a Data warehouse. The planning process takes in to consideration Data Profiling and Data Quality as knowing which of your data is the natural starting point of building a successful data warehouse.
Some of the other critical steps observed by SQIAR in planning a successful Data warehouse strategy are:
- Data integration and reconciliation
- Data quality and master data management (MDM)
- Iterative delivery
- “Packaged” data warehousing applications
- Data warehouse/ Application performance
- Deployment and change management
Query, Reporting & Analysis – Providing 360º Business View
If business intelligence (BI) is about enabling corporate decision makers to navigate today’s complex business environments, the focus of BI solutions should be more about the user and less about the technology. The BI industry has spent decades perfecting the process of data collection, storage,
cleansing and distribution – with good reason considering the mounds of data massed in corporate data stores today. Taking BI to the next level means not only transforming data into information, but also getting it into the right hands, at the right time and in the correct format to be used for timely decision- making. The BI industry has come to a crossroads, and it is time to re-engage with the business community to better understand each user and their role in the Enterprise.
Scorecarding & Dashboarding- Empower the Business User
You have mountains of data and multiple tools to move, analyze and distribute it. But getting the right bits of information to the right professionals at the right time is still a hit-or-miss proposition. Even when you think you’ve got the right technology in place, users resist adopting it. Vendors keep pitching new-and-improved feature-laden solutions, but can you justify the expense for what could become yet another underutilized tool? Is there a future in all these features? Or is less the way to deliver more? The problem is simple. It’s complexity. Unfortunately, the solution – more simplicity – is complex and difficult to achieve. But simplicity has always been key to the adoption of new technologies. Mooers’ Law: “An information retrieval system will tend not to be used whenever it is more painful and troublesome for a customer to have information than for him to not have it.” The 3 pillars of simplicity that apply to effective scorecarding are:
- Easy to use Interface
- Usable Features
- Ease of Deployment and Administration
It’s About the User
There is a disconnect in the current BI delivery model between decision support tools and the decision-making process. On the IT side, we continue to make incredible progress on data storage, integration, access and delivery. However, line of business users – the business decision maker, isn’t interested in the success in this area; their primary concern is answering such questions as:
- Which customers are most profitable? Why so? How to raise Profitability of customers who fall short?
- Is there enough inventory on hand to fulfill orders? If so, what downstream impact should we be prepared for with other orders?
- What product or service offerings will best drive our revenue goals this quarter?
- What is the right offer in terms of product mix, cost and pricing to preserve our gross margin requirements while we grow?
- Where should we be focusing our sales people at this time? Do I need to split territories.
Strategic decisions, on the other hand, are most often made at the executive and upper management levels within the organization. Because strategic decisions can impact many divisions and functional areas within the business, they occur less frequently than day to day tactical decisions. Strategic decision support usually means providing consolidated and cross functional data. The analysis of data necessary for strategic decision-making often leads to additional questions, which ultimately means additional requests for data. Examples of Strategic Decisions:
- Should we enter the market with this new product line?
- What distribution channels should we pursue in global markets?
- Do we put market share or profit margin at the top of the priority list for the next two years?
- Does that mean additional marketing budget allocations or investing in Manufacturing efficiencies or new product development?
Knowing whether the user at hand typically makes tactical decisions, strategic decisions or both, will help frame your decision support solution.
Our Data Warehouse services ensures:
Data transferred from operational systems into the data warehouse are examined and corrected in order to obtain reliable and error-free information, as much as possible.
Queries aimed at extracting information for business intelligence analysis are optimized to maximise performance without compromising the level of detail your analysis may require
Data from all business sections are sourced into a central Data Warehouse to support both micro and macro level desicion making. Aditionally you never loose track of historical data so that your decisions are firmaly based on knowledge from past, present and future
During a business intelligence analysis, orientation toward the entities allows the performance of a company to be more easily evaluated and any potential source of inefficiencies to be detected.
We make sure that your data fully incorporates all your business knowledge and is tightly knitted around core entities of interest for the analysis
The data originating from the different sources within your business or even any interesting nuggets of data available from external sources are integrated and homogenized.