Analyzing Information to Gain Business Insight

Multi-Dimensional Analysis – Data Discovery

Bardess consultants will analyze your multi-dimensional data beyond the traditional ad hoc query analyses on static data in a warehouse or operational system. We will use Business Discovery and Advanced Analytical tools to navigate through your data – discovering patterns, trends and information from various points of view. We will drill down to different layers of information, slice-and-dice data in different combinations and from several perspectives, and use graphics to visualize key variables driving business results.

Bardess will use a variety of methods to access your corporate data depending upon the existing systems and data architectures. The methods may range from structured SQL Queries to a data warehouse or operational system, the use of Business Discovery BI tools like QlikView or Spotfire to extract, aggregate and sort data into a format for analysis, or the use of advanced analytical tools to predict outcomes and determine optimal solutions.

Outputs: 

  • Analytical Reports
  • Statistical Analyses
  • Trend Analyses
  • Analytical Models

BI Data Assessment and Validation

Before developing Business Intelligence solutions, Bardess will ensure that the data you are collecting is valid and accurate for the development of management and operational reports and metrics. We will perform a targeted series of steps using data management and Business Discovery tools to analyze the data flows and compile meaningful information.

Outputs: 

  • Analyses of Data Flows
  • Assessment of Data Stores
  • Validation of Data Between Stores
  • Determination of Data Confidence Levels
  • Data Mapping and Translations
  • Data Compilation

Advanced Analytics — Data Mining and Statistical Analysis

Bardess will use statistical and mathematical techniques and algorithms to mine your databases for hidden information. We will perform statistical analyses to identify meaningful patterns within the data and to locate and eradicate non-quality data.

Using Advanced Analytical and mining tools such as SAS, R, or St, we will apply common techniques such as Association, Sequence, Classification, Regression, Cluster Analysis, and Time Series Forecasting. Our statisticians will use the tools to build the targeted analytical models for mining operations.

The most common types of Mining that will be used include:

Link Analysis
Used to find relationships between selected items in database records
Classification Modeling
Used to predict a given event by sifting through data and uncovering variables that identify classes of information
Database Segmentation
Methods to group related data records into meaningful segments
Deviation Identification
Method to identify records that are not typical and identify potential reasons for the anomalies

Outputs: 

  • Tables with Mining Analysis Data
  • Trend Analysis
  • Statistical Models