Business Intelligence (BI) & Analytics Software

Business Intelligence Balanced Scorecard
A Balanced Scorecard is a performance management tool that summarizes an organization’s performance from multiple perspectives on a single page. It provides the decision makers with a great overview of KPI’s (key performance indicators). A Balanced Scorecard integrates performance measures into the basic management structure of the organization. TARGIT BI Suite enables users to monitor and analyze business performance in categories such as financial performance, customer knowledge, business processes, and learning and growth.

Business Intelligence (BI)
Business Intelligence primarily refers to computer-based techniques for identifying, extracting, and analyzing business data. Examples of such data could be revenue by products, no. of sales by person or period, purchasing orders and much more. Business Intelligence provides historical, current and predictive views of your company. Typical BI functions are reporting, analytics, data mining, performance management, benchmarking, and predictive analytics. The purpose of Business Intelligence is to support better decision-making throughout your organization. And TARGIT aims to help you make those decisions in the fewest clicks. Business Intelligence extracts data from any type of data source and platform. Examples are: Microsoft Dynamics portfolio, MySAP, SAP Business One, Oracle, Salesforce, Excel-sheets, CS5, AS400 etc.

Learn about important features in TARGIT’s Business Intelligence solution, TARGIT BI Suite.

Business Analytics
While Business Intelligence answers questions such as what happened, how many, how often, where the problem is, and what actions are needed, you need to do business analytics to find out why is the issue happening, what if the trends continue, what will happen next (predict outcome), what is the best that can happen (optimize). Without Business Intelligence it is difficult to spot the important issues that sits in your mine of company data.

Business Intelligence Cube
A (Data) Cube is a multidimensional structure that forms the basis for analysis applications. Cubes can have multiple dimensions and allow for a variety of calculations and aggregations.

Business Intelligence Dashboard
A Dashboard in Business Intelligence has visual similarities to a car dashboard. It is a user interface that organizes and presents information in an easy-to-read format and help organizations align people’s actions with strategy by monitoring and analyzing key performance indicators (KPIs). Dashboards and scoreboards enable proactive management with “what-if” analysis, customer segmentation, and analyzing business processes. It provides graphical depictions of current KPIs in order to enable faster response to changes in areas such as sales, customer relations, performance assessments etc. on a single screen.

Customer Relationship Management (CRM)
Customer relationship management (CRM) describes both a business process and an associated software application family. CRM is an implemented strategy for managing an organization’s interactions with customers, clients and sales prospects. When doing CRM, you typically use technology to organize, automate, and synchronize business processes. CRM is used for finding, attracting, and winning new clients, nurturing and retaining those the organization already has, entice former clients back into the fold, and reduce costs of marketing and customer services. Customer relationship management is part of a company-wide business strategy. Named software examples: Microsoft Dynamics CRM, SuperOffice, Salesforce, SAP, Oracle etc.

Database
A database has the same characteristics as a data warehouse, but is usually smaller and is focused on the data for one division or one workgroup within an enterprise.

Data Mart
A data mart (DM) is a specialized version of a data warehouse (DW). Like data warehouses, data marts contain a snapshot of operational data that helps business people to strategize based on analyses of past trends and experiences.

Business Intelligence Data Mining
Data Mining is a component of business intelligence. It relates to discovering previously unknown patterns within a data set, typically by testing the validity of different ways of describing the data. Data Mining is an iterative, quantitative process of identifying potentially useful, valid, and new patterns in data, usually for the purpose of prediction (See Predictive Analyses below).

Data Quality
Data quality pertains to aspects such as availability, completeness, accuracy, consistency, relevance and timeliness of data. High data quality is essential to business intelligence’s role as a means of decisional support. Poor data quality examples: missing fields, old or inaccurate information, data conflicts, inaccessible data in legacy systems. Often, even when working with the best data sources, an element of data cleansing is necessary to obtain a data quality that is suitable for analytical purposes. If your data is not of the right quality, you will not be able to create comprehensive analyses.

Data Source
A data source is a facility for storing the data. It can be as complex as a database for a large corporation or as simple as an Excel spreadsheet with rows and columns. A data source can reside on a remote server, or it can be on a local desktop machine. A Business Intelligence solution accesses a data source using a connection. Examples are: Microsoft Dynamics portfolio, MySAP, SAP Business One, Oracle, Salesforce, Excel-sheets, CS5, AS400 etc.

Business Intelligence Data Warehouse
A Data Warehouse (DW) is a database that is geared toward the Business Intelligence requirements of an entire organization. The data warehouse integrates data from the various operational systems (see Data Source) and is typically loaded from these systems at regular intervals by means of automated ETL procedures (see ETL). Data warehouses contain historical information that enables users to analyze business performance over time.

Business Intelligence Dimension
A dimension is one of the perspectives that can be used to analyze the data in an OLAP cube. Dimensions are used to categorize and filter the measures (see Measure) of your cube. When you are browsing the data in a cube, dimensions can be combined to view the data from different perspectives. For a Sales database, the dimensions could include Product, Time, Employee, and Customer. Dimensions are defined by attributes which are individual categorization options. Attributes may be combined into one or more hierarchies with increasingly detailed information, giving the end user options for easy drilling up and drilling down in the data.

Business Intelligence Drill Down
Drill down is a component of OLAP analysis. The term drill down refers to the process of navigating from less detailed information to viewing more specific data.

Business Intelligence Drill Through
Drill through is an action in which you move horizontally between two items via a related link. An example to drill through is in the case of two reports that are in a master /detail relation with each other, and by clicking a master item on the master report you reach the details of the clicked item on the details report. Example: You are looking at a highly summarized number, e.g. the total revenue for selling Jeans in Europe last month. A Drill Through on this number will open a detailed report with all the transactions that forms the basis of the summarized number.

Enterprise Resource Planning (ERP)
Enterprise Resource Planning systems integrate management information across an entire organization, embracing finance/accounting, manufacturing, sales and service, customer relationship management, etc. ERP systems automate this activity with an integrated software application. Their purpose is to facilitate the flow of information between all business functions inside the boundaries of the organization and manage the connections to outside stakeholders. ERP systems can run on a variety of hardware and network configurations, typically employing a database as a repository for information. Named software examples: Microsoft Dynamics NAV, AX, GP & SL and MySAP, SAP Business One, Oracle etc.

ETL (Extract, Transform, and Load)
ETL is the process of getting data out of one data store (Extract), modifying it (Transform), and inserting it into a different data store (Load). In Business Intelligence projects, ETL packages are used to extract data from the data sources and load it into the Data Warehouse and subsequently into the cubes – with possible transformations on its way. Various tools are available for designing ETL packages, and once an ETL package has been designed it is often scheduled to be run automatically at fixed intervals, e.g. once every day.

Business Intelligence KPI (Key Performance Indicator)
KPIs are commonly used by organizations to evaluate activities and processes. Examples of KPIs are: Revenue, Employee Satisfaction, Web Traffic, Turnover Rate etc.

Business Intelligence Measures (in OLAP)
A measure is a numeric value stored in a fact table and in an OLAP cube. Examples of measures in an OLAP cube could be Sales Count, Sales Price, Cost, Discount, and Profit.

Metadata
Metadata is data that describes and enriches the data in the warehouse. As an example, metadata can be used to translate the business terms in the Data warehouse in an organization with employees in multiple countries.

MOLAP (Multidimensional OLAP)
MOLAP refers to performing OLAP using multidimensional databases (see Cubes).

OLAP
OLAP is short for On-Line Analytical Processing. It is an approach to building analytic solutions that enables the analyst to interact with information that has been transformed from normalized data into a form that highlights business dimensions and often has a time based dimension. OLAP business dimensions are often organized into hierarchies that facilitate drill down to detailed views or roll up to higher level values.

Business Intelligence Predictive Analytics
Predictive Analytics exploit patterns found in historical and transactional data to identify risks and opportunities. TARGIT BI Suite use Sentinels (TARGIT Patent) to give you an early warning. Sentinels warn you about possible changes in advance by expanding the timeframe for the notification agents in your TARGIT Business Intelligence solution.

ROLAP (relational OLAP)
ROLAP refers to performing OLAP using relational databases.