Pivot Grid and charts
Hovitaga Data Visualizer can display data with a pivot grid for intuitive OLAP analysis. No technical knowledge is required, simply drag and drop your data to form rows, columns and numbers. Sorting, filtering, grouping and drill-down is quick and easy with Hovitaga Data Visualizer. A chart can be switched on and off which displays the contents of the pivot grid. It is updated automatically with every action (drill-down, filter etc.). The chart can be customized (type, appearance) to provide the best visualization possible.
Most business data has some sort of geographical meaning. Business partners, customers have addresses, sales organizations are assigned to geographical territories and so on. Displaying the right data on a map is vital to see correlation between your numbers and geographic positions. Simply drag and drop your data on the map to create heatmaps or to plot shapes on the map. Size, color can be binded to data fields (for ex. total sales determines size, product group determines shape and revenue determines color), or even piecharts can be drawn to coordinates. Data can be aggregated on different levels dynamically (continent, country, state, city, postal code or rooftop), the maps are updated immediately. Microsoft Bing Maps and Openstreetmap can be used for tile-based maps and any shapefile can be used for heatmaps. This is possible even if you don’t have coordinates stored in your database. Simply select the fields that store address data and Hovitaga Data Visualizer automatically uses Microsoft Bing Spatial Data Services to obtain the coordinates for the given address.
Using treemaps is very effective to gain an overview on a lot of data quickly. Treemapping is a method for displaying hierarchical data by using nested rectangles. The size and color of the rectangles is determined by data fields chosen by the user. When the color and size dimensions are correlated in some way with the tree structure, one can often easily see patterns that would be difficult to spot in other ways. A second advantage of treemaps is that, by construction, they make efficient use of space. As a result, they can legibly display thousands of items on the screen simultaneously. Treemaps can be created with drag and drop, navigation between levels is easy with simple mouse clicks.
Simple list and chart
Tabular data can be displayed in the conventional list format. The list can be sorted, filtered and grouped with a few clicks. Just like with the pivot grid, a chart can be displayed which visualizes the contents of the list.
Summarized information can be visualized perfectly with gauges. The appearance of gauges can be customized and data can be bound to the indicators of the gauges. Gauges are especially effective on dashboards to provide summarized information which is easy to interpret.
Dashboards can be created in seconds: place any number of containers on the screen, position, align and resize them as you wish, and define the content of each container. You can use your previously saved maps, lists, charts, treemaps, pivot grids and gauges to put them in the containers on the dashboard. You can change the dashboard during runtime, hide/show/resize containers etc. Naturally one dashboard can use multiple data sources.
The most important feature of Hovitaga Data Visualizer is that no programming effort is required at all in the SAP system. Any SAP Query or report that has the standard structure (selection screen and a list output) can be used immediately, right out of the box. It is also possible to use SAP tables and views directly as data sources. Hovitaga Data Visualizer can directly connect to SAP Business Warehouse through its XML for Analysis interface and visualize InfoCube queries.
Every connection needs a SAP user and password to be provide, but multiple connections can be made with the same user at once.
Our other product, Hovitaga OpenSQL Editor can be used as a data source to provide a real ad-hoc query solution: simply write and SQL query against the SAP system and immediately visualize it with charts, maps or pivot grid.
No ETL necessary
ETL stands for Extraction, Transformation and Loading, which is the end to end process of gathering all data in the right format for analysis. This is a very complicated, high-effort activity that every BI solution needs to accomplish.
Hovitaga Data Visualizer drastically reduces the ETL process almost down to zero. The concept is that every BW InfoCube query, SAP report or query and table already has every necessary metadata stored in SAP. Hovitaga Data Visualizer reuses this information and does not need any additional mapping, transformation or customizing. In case of using SAP BW, metadata is automatically read along with the business data. In case of flat data (reports, tables, queries) there is an automatic process of making the flat data multidimensional. Fields are classified as measures or dimensions based on their data dype. This automatic proposal can be overridden, but only needed to be done once since the settings can be saved for each data source.