Benefits of Choosing ABI to Accelerate Decision Making 

Companies create and sustain competitive advantage, in part, by utilizing knowledge gained from operations, R&D, and competitive analysis. Organizations that use ABI platforms benefit from: 

• • • • Faster and more accurate reporting, analysis, and planning 
      • Better business decision making 
      • Improved data quality 
      • Increased operational efficiency 

By choosing ABI, companies can perform advanced analytics to gain deep insights into business processes. Key components of analytics include: 

• • • • Data Aggregation 
      • Data Mining 
      • Association and Sequence Identification 
      • Forecasting 
      • Predictive Analytics 
      • Data Optimization 
      • Data Visualization 

Business Intelligence and Data Integration Analysts 

Business intelligence and data integration (BI/DI) analysts use analytics to transform available data into valuable insights for companies. These specialists straddle the worlds of business and information technology, enabling them to mine and analyze data, as well as recommend strategies for a company. 

BI/DI analysts help companies put data to use in order to increase the company’s efficiency and maximize profits. They have a range of skills, including data mining and analytics, a keen business understanding, and the ability to create conceptual and logical data models. 

An effective BI/DI analyst must have a specialized skill set. The abilities to manage implementation and support teams, provide effective database designs, and develop conceptual and logical data models are key. Data mining and general analytical skills are also important. 

Since BI/DI analysts work with teams, they rely on excellent communication and presentation skills. Along with the ability to document requirements, analysts who specialize in business intelligence and data integration need to be innovative and use creative problem-solving skills and critical thinking. 

4 Key Parts of a Successful ABI Implementation

1. Business understanding and requirements  

Requirement-gathering sessions with stakeholders within the organization are a must. Conflicting requirements within the organization must be identified and resolved as part of the stakeholder approval process.  

The goal of this step in the project is to clarify the answers to key business questions, some of which include: 

• • • • What are the business objectives? 
      • What are the metrics for success for those objectives? 
      • What are the constraints and risks? 
      • What are our business assumptions? 
      • Who are the stakeholders? 
      • What are our resources? 

Resource requirements and planning steps need to be outlined to create a project plan that will be managed with both internal and external resources. 

2. Data understanding and data quality audit 

Collecting initial data, and then analyzing and describing the data, will provide a basis for assessing its level of quality. This phase results in the delivery of a data dictionary, a logical data model, and data-mapping documents. 

Early investment of effort in a data quality audit saves time and money. Key concerns focus on addressing important questions that include:  

• • • • What are the specific characteristics of the data sources in question? 
      • What is the gap between the existing and desired level of data quality? 
      • What is the estimated level of effort required to close the data quality gap? 
      • What data anomalies can be identified? 
      • How can the impact of data anomalies be minimized? 

3. Solution design and development

The solution design and development is typically led by internal IT or third-party contracted resources. The business requirements document, logical data model, and source-to-target mapping are utilized in creating the data warehouse and data marts along with the integration of third-party reporting/data mining applications. 

End user application training is conducted as the last phase prior to the production rollout. This training should include guidance on proper use of the implemented solution, as well as testing with actual data for user acceptance. Test cases written by team members or the BI/DI analyst are used to validate that business requirements have been met. 

ProActive is the Right Partner for Your ABI or Data Integration Project

ProActive Solutions has dedicated over 20 years to providing customers with the insight to make quality business-critical decisions faster. We've helped organizations in a variety of industries resolve challenges with data quality and governance, sourcing and extraction, transformation, and data warehousing by designing, delivering, and supporting successful ABI solutions.

ProActive has extensive experience integrating data from a variety of services and technology platforms, including cloud, Linux, Windows, Kubernetes, and IBM platforms, as well as working with a variety of data integration, analytical, and business intelligence tools. We partner with technology leaders Red Hat, IBM, Microsoft, and others.

If your company has business processes that are hampered by an ineffective BI implementation or you need assistance with integrating your business data, our specialists can help. 

Find out more about what ProActive does to support BI and our other Business Solutions. Check out our Customized Business Services Page.