Data Management Tools
Better decision-making starts with better data. Data management tools help clean up "dirty data," organize information by providing format and structure and prepare databases for analyses.
Data quality management
- Helps organizations maintain clean, standardized and error-free data.
- Standardization is especially important for BI implementations that integrate data from diverse sources.
- Data quality management ensures that later analyses are correct and can lead to improvements within the business.
Extract, transform and load (ETL)
- Collects data from outside sources, transforms it and then loads it into the target system (a database or warehouse).
- Because primary data is often organized using different schemas or formats, analysts can use ETL tools to normalize it for useful analysis.
Data Discovery Applications
Data discovery applications help users make sense of their data, whether it be through quick, multivariate analysis during OLAP or via advanced algorithms and statistical computations during data mining.
- Sorts through large amounts of data to identify new or unknown patterns. It is often the first step that other processes rely on, such as predictive analytics.
- Databases are often too large or convoluted to find patterns with the naked eye or through simple queries.
- Data mining helps point users in the right direction for further analysis by providing an automated method of discovering previously neglected trends.
Online analytical processing (OLAP)
- Enables users to quickly analyze multidimensional data from different perspectives.
- It is typically made up of three analytical operations: data consolidation, data sorting and classification ("drill-down") and analysis of data from a particular perspective ("slice-and-dice").
- Analyzes current and historical data to make predictions about future risks and opportunities.
Semantic and text analytics
- Extracts and interprets large volumes of text to identify patterns, relationships and sentiment.
In the words of John W. Tuckey, “the greatest value of a picture is when it forces us to notice what we never expected to see.” Reporting applications are an important way to present data and easily convey the results of analysis.
- Helps users create advanced graphical representations of data via simple user interfaces.
- The ability to visualize information in a graphical format
- Dashboards typically highlight key performance indicators (KPIs), which help managers focus on the metrics that are most important to them.
- Dashboards are often browser-based, making them easily accessible by anyone with permissions.
- Scorecards attach a numerical weight to performance and map progress toward goals.
- Think of it as dashboards taken one step further (e.g., balanced scorecard, Six Sigma etc.)