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Data Analysis

CDI Technologies Business Intelligence stack addresses multiple data analytics issues. It offers the needed tools for data collaboration, gaining insights, and transformation and is equipped with powerful enterprise governance features so you can use BI with fine-grained security.

  • CDI-BI is made up of a series of modules that enable you to create and share a range of analytic content with your end users, whether as a solution for enterprise analytics, as an OEM BI tool for embedded analytics or as a stand-alone analytical application that is a specialist vertical data solution. In this section each of the core components is described and its associated use cases.
  • CDI-BI does not require you to import data, rather it works with data in your existing data sources. Several main types of data store are supported:

    ·       JDBC compliant databases such as SQLServer, Oracle, Exasol, Snowflake, Redshift, Progress Open Edge and many more.
    ·       XML/A compliant cubes such as Microsoft Analysis Services, SAP BW, Oracle Essbase.
    ·       CSV files (which are then loaded into a relational database).
    ·       Third-Party sources including applications like, Google Analytics and many others.
    ·       Configuration data is stored within the CDI-BI database, but reporting data is stored separately. For optimum results, it’s recommended to use a fast dedicated reporting database which uses technology designed for high-speed analytics. This may include columnar storage, in-memory processing, massive parallel processing, or other approaches.
    ·       The system is highly flexible and can be deployed in the cloud, on-premise or as part of a hybrid approach.
    ·      YCDI-BI uses meta-data to generate the appropriate, optimized queries for each type of data source. Data can also be retrieved from stored procedures that output a table object. Further, reports can be written that combine data from multiple data sources.
    ·      Plugins allow for data to be extracted from any source via an implementation of Third-Party Java API. In that way custom connectors can be written to connect to data sources not currently supported.

Plenty of plans, no hidden fees at all.

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Any questions? We have the answers.

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Read our FAQ

Data Transformation

CDI-BI has a complete ETL module that allows you to extract data from any supported source, transform that data using a variety of transformation steps, and write the output to any supported write-able database target. This capability is useful when the data you are accessing requires some degree of manipulation or enhancement in order to make it more suitable for analytical purposes. For example, this could involve:

  • Blending data from disparate data sources together into a single physical table (for example, transforming data from a 3NF model into a star-schema, or aggregating data for faster performance).
  • Converting data elements into a more useful form, such as transforming the data type of columns, manipulating the data in columns, creating calculated fields.
  • Enhancing data by calling custom transform steps – for example to add external data (such as weather or geocoding points) or calling a data science model to calculate a prediction.
  • Eliminate under and over payments, as well as unrecorded and duplicate payments, maintain a clear and concise audit trail store all pertinent customer data in a customer profile, ensuring that sales documents contain the correct payment terms, contact information, ship-to address and shipping method.
  • Custom transform steps can also be created and imported into CDI-BI.

Data Science Integration

Custom developed data science models can be integrated into CDI-BI via an ETL flow or directly into a report. In this way, new data such as a prediction can be integrated into your analytics solution.

CDI-BI can connect live to models hosted in R,, AWS Sagemaker and can natively run models exported in PMML or PFA formats.

A model can be embedded as a step in an ETL flow – this allows the predicted value output from the model to be written once to a database of your choice. Alternatively, a model can be run live from within a report using an advanced function.

Both the ETL steps and advanced functions are extensible. Customers can write their own code and import it via the plug-in manager if their modeling platform is not currently supported.

Meta Data Modeling

CDI-BI provides a comprehensive modeling layer to capture the technical and business information about your underlying data. CDI-BI uses this information to provide a business-friendly layer to end-users, whilst using the technical information to generate the relevant queries.

Meta-data modeling is performed using a friendly drag and drop interface. The data relevant for reporting can be identified, technical information such as data types, join conditions and so on can be defined, business names, definitions and default formatting can be applied, and additional information can be derived such as data grouping or complex calculations. CDI-BI can analyze the underlying data and generate recommendations on what steps should be performed to prepare data for analysis.

Once defined, this meta-data underpins all other CDI-BI processes. It need only be defined once and shared by everyone. This ensures a consistent approach to using data across your whole system.


Once the meta-data is defined for an underlying data source, reports can be built using the drag and drop report builder. The report builder allows the creation of simple tabular reports through to incredibly complex queries (for example, correlated subqueries, unions, crosstabs etc.). CDI-BI uses the report definitions to generate query syntax in the appropriate language of the underlying data source. The complexity of defining joins and other syntax is hidden from the user – although the generated queries syntax can be accessed. If desired, queries can be written using free-hand SQL.

Filters, aggregations, calculations, advanced statistical and analytics functions can all be defined in the query. Reports can be visualized as standard tabular reports, as one or more charts, or as a collection of objects on a free-form design canvas (infographic).

CDI-BI’s Assisted Discovery capability can be used to run statistical algorithms against the underlying data in order to automatically identify interesting correlations and associations in data, and to automatically generate a set of visualizations to help accelerate your analysis

Data Visualization

CDI-BI supports a wide-variety of ways to visualize report output. This includes tabular or cross-tabular reports, one of the many out of the box chart types, or a custom JS chart of your choice.

Users can interact with visualizations in a variety of ways – including drilling down a hierarchy, drilling through into a detailed report, applying filters to narrow down on the data required, using tooltips to show more information, brushing data to select and restrict areas of interest, exporting data to one of the wide-variety of supported sources (including Excel, PDF).

Reports can be shared with others or scheduled to be broadcast and distributed to one or more users on a regular basis. Further, rules can be defined which indicate when a report should be sent, for example when a key metric passes a threshold.


A dashboard provides at-a-glance views of key performance indicators (KPIs) relevant to a particular objective or business process.  Typically, multiple reports and visualizations are combined together to form a Dashboard.

CDI-BI provides two main ways to create Dashboards – using pre-set layouts (in which report, and chart content can be dragged and dropped into predefined positions) or Canvas layout (a free form layout where multiple types of content can be freely positioned to create rich designs). As well as reports and charts, Canvas layout supports additional objects such as text, images, icons, filter objects, action buttons and more. Canvas mode has the additional benefit of allowing access to code-mode. Code mode allows developers the option to extend the dashboard functionality with custom-code (JavaScript, html, CSS) to create custom objects and navigation experiences, as well as connecting and invoking functionality in third-party applications.

CDI-BI Dashboards can contain data from multiple data sources, and each object can be connected to a single set of common filters. Further, user actions in one visualization (such as a brush or drill) can be used to initiate actions in other visualizations (filtering, drilling).

Automated Monitoring & Data Discovery

CDI-BI has developed advanced machine learning capabilities that assist users in the discovery and interpretation of AI driven data insights. These capabilities augment the capabilities of the user and enable them to analyze more data, find more insights and understand root cause – far faster than a human alone ever could.


CDI-BI Signals can be used to automate the process of discovering important insights in your data. Signals leverages the meta-data layer and can be easily configured to continually scan your data, identify changes that exceed thresholds, and create personalized notifications to your users.

Assisted Insights

Assisted Insights capability is accessible from reports and dashboards. With a simple right click, any user can invoke a powerful set of algorithms to automatically analyze the data they are currently viewing to identify hidden underlying patterns and drivers. For example, a user may see a spike in a line chart for one period – assisted insights can be used to analyze that spike by comparing it with a prior period. The analysis will determine the key drivers that led to the differences between those two periods and present those as a series of insights – ranked by statistical relevance. Each insight is accompanied by an automatically generated visualization, and a set of natural language descriptions of the finding. These insights can be saved and shared with other users.

Assisted insights can be enabled at the view level with some simple configuration steps.

Assisted Discovery

Assisted Discovery is available in the CDI-BI Report builder and can automatically analyze data to identify important and relevant correlations. This can rapidly accelerate the work of a data analyst for example, who may be analyzing a set of data for the first   time.

A series of algorithms are run over selected data, and insights are generated and displayed as a series of automatically generated visualizations and natural language  narratives. The analyst can select the insights that they are most interested in, and instantly add those to the chart builder. These charts can then be shared, scheduled, or combined into a dashboard.

Threshold Alerts

Individual reports can be scheduled to be run and distributed on a regular basis. Rules can be set against those reports which define when the report should be sent. This allows for example, reports to be sent on an exception basis – say when a particular metrics exceeds or falls below a predefined threshold. Rules can be set on the total value of a metric in a report, or triggered when any row in a report exceeds the threshold.

Mobile & Collaboration

The CDI-BI mobile app allows you to stay up to date on the go.

Built with a familiar social media feel – the app experience is centered around a feed. The feed provides everything that users need to stay up to date – including alerts about new Signals, published Stories, mentions in discussion threads and notifications on new content (reports, dashboards).

With a simple self-onboarding experience, and integration with biometric authentication on your Apple iOS or Android Mobile device, getting up and running with mobile is simple and fast.

The mobile experience is fully interactive and enables users to easily share insights across the organization. All the common app capabilities are there – including liking, sharing, commenting, posting, connecting, and following others.

The future of Supply Chain Management is here,
are you ready for it?