Go Beyond Simple Reporting

To compete, today's organizations must rely on data-driven decision making. Unfortunately, conventional spreadsheets and databases don't know how to automatically extract valuable knowledge from raw data. For years, large companies (ex: banks, insurers, retailers) have reaped the benefits of data mining to optimize their business. However, because of tremendous complexity and high costs, automated analysis has remained out of reach for small and medium businesses. Data Applied is changing the rules of the game by offering affordable, Web-based Data Mining and Business Intelligence solutions. Did we mention it's all programmable?

Consider a data set containing hundreds or thousands of rows such as these:

Age Sex Zip Income Married Mortgage Occupation Transactions Balance Signed up ... Defaulted
28 Male 98052 True False 18422.50 Construction 47 1147.14 05/17/2003 ... False
35 Female 98074 False True 14750.00 Finance 12 3476.40 08/04/2005 ... True
... ... ... ... ... ... ... ... ... ... ... ...

Unless you're a banker, your own data probably looks quite different. However, suppose your goal is to understand which customers default on credit. Using conventional spreadsheet software, you would need to plot hundreds of charts to see how different combinations of variables affect credit default (ex: married + male + age 20-25 + two cars = 80% default). By comparison, Data Applied's automated analysis systematically examines all combinations, and finds groups with a higher probability of default. Other types of automated analysis are also possible: spot anomalies, categorize customers, pinpoint key influences, compare by demographics, etc. It's time to go beyond simple reporting!

Other solutions:

Data Applied:

  • Is analysis limited to data visualization?
  • Is installing software on each client required?
  • Is the solution single-user?
  • Is purchasing a new database system required?
  • What are the hidden training & consulting costs?
  • Does the solution have to be deployed internally?
  • Is pricing based on the number of processors?
  • How can the solution be made to scale?
  • Can data & analyses be shared securely with others?
  • Can analysis results be searched, or are they static?
  • Is the solution programmable / scriptable?
  • How can analysis results be exported?
  • How is large data handled (ex: must fit in memory)?
  • Any restrictions on data (ex: numeric values only)?
  • Are binaries available in 32 bit only?
  • Need to request a quote to get a price?
  • Data visualization + automated analysis + data mining
  • Zero footprint Web browser access
  • Multi-user client / server architecture
  • Open source (MySQL) or commercial (SQL Server)
  • Rich intuitive user interface = rapid user adoption
  • Public cloud, private cloud, or local intranet
  • Hardware-independent pricing model
  • Easily add servers for load-balancing / scale out
  • Numerous user collaboration & security features
  • Pervasive search & drill down capabilties
  • Comprehensive XML-based Web API with library code
  • Export as text, presentation-ready images, or via the API
  • Scalable algorithms, data streaming, distributed computing
  • Algorithms handle missing, categorical, and numeric values
  • 32 bit, or 64 bit for up to 16 TB addressable memory
  • Clear, transparent pricing policy (see our Web Store)

Share Data and Analyses

Perform collaborative analysis by securely sharing data sets with others. Decide who has access to what, and with which access level. Export analysis results to a searchable timeline. Tag data and analysis result with comments and keywords. Download analysis results as text or as presentation-ready images. Visualize & rate results exported to the gallery.


Visualize Large Data Sets

Visualize large amounts of data using tree maps. Rectangular tiles are used to represent individual records and obtain a global perspective of the data. Users can specify which fields should be used to color and size each tile. In addition, tiles can also be organized into groups. Search can be used to perform drill down explorations.

Tree Maps

Identify Hidden Associations

Automatically identify associations hidden in your data. Associations which are stronger than expected (assuming independence between variables) are identified and reported. Each association is fully specified by its strength, the number of records affected, and its preconditions. Users can easily retrieve the list of matching records for further analysis.


Visualize Correlations

Automatically compute and visualize correlations between numeric fields. Correlations between each pair of numeric fields is calculated, and rendered as a graph. Filtering, area selection, and automatic group detection makes it possible to easily identify groups of highly correlated fields, or fields with little influence on others.


Discover Similarities

Automatically visualize similarity between records. Records are projected onto a two-dimensional map, in a way which attempts to project similar records to closeby cells. As a result, users can easily find which records are similar to any given one. The group identification feature allows discovery of broad categories of similar records, while the cell profile feature makes it possible to view the profile associated with each cell.

Similarity Maps

Detect Anomalies

Automatically detect true anomalies, or valid but exceptional cases. Using a powerful algorithm, records which are the most different from their closest neighbors are quickly and systematically identified. Users can visualize those records and their neighbors, for example to address data quality or fraud issues.

Outlier Detection

Build Powerful Reports

Generate pivot reports on steroid using multi-level grouping. Each intersection between a vertical and horizontal group yields a different chart. This allows users to perform visual comparisons between groups. Users can easily switch between scatter plot, bar chart, pie chart, graph line, and heat map visualizations. Search can also be used to further refine views.

Super Pivots

Pinpoint Key Influences

Automatically determine which fields most influence others, and under which conditions. Decision trees show how the distribution of a given target variable changes, depending on values taken by other fields. For the field having the most impact on the target variable's distribution, a new split is created, showing how the target distribution was affected.

Decision Trees

Transform Your Data

Easily prepare or transform data by specifying a set of transformation steps. Create, rename, delete, or convert fields. Filter, sample, or rank rows. Scramble values, compare values, use complex formulas and dozens of built-in functions. Use rule-based editing to execute powerful data transformation without having to write a single line of code or script.


Forecast Time Series

Automatically forecast time series. A neural network algorithm is trained using all available data, allowing it to detect and learn patterns such as seasonal variations, underlying general trends, or user activity patterns. Monte Carlo error simulations are used to evaluate the stability of the model, and visualize possible variations.

Time Series Forecasting

Categorize Records

Automatically discover broad categories of records using a cluster detection algorithm. The clustering algorithm finds groups of records sharing common traits, and generates profile information for each group. Users can then visualize these clusters as nodes, as well as their resemblances or differences. For each cluster, users can also view a profile of member records, and a profile of records lying outside of the cluster.


Protect Your Data

Users can be granted different access levels to different workspaces and data sets (ex: grant read, write, or full access). Security is enforced at the server level, so there is no way to bypass access checks. As a result, security is also enforced for any applications which uses the XML Web API to perform remote data analysis or processing.