Information is key. Dimensional Insight’s award-winning Diver Platform builds solutions that help users get the information they need in a format they can understand.
Diver Platform’s data integration is easy to use
Diver Platform’s enterprise data management software helps you overcome a challenge that most businesses today face — making the right decision when your information is based on data that is a mess. The complex nature of business today means that organizations often employ many disparate sources to capture the data they need. Assembling that data into a single actionable format is difficult, costly, and time-consuming, preventing key decisions from being made in a timely fashion. That all changes when you use Diver Platform.
Diver’s flexible end-to-end enterprise-wide reporting and analytics provide all of the components needed to implement and deploy actionable, role-based business intelligence across your organization. Diver’s world-class quality enterprise solutions make data integration easy. It gives all stakeholders a complete understanding of the data, enabling you to identify insights and transform those insights into measurable actions.
Data Integration That Provides Optimum Performance
Diver begins with Integrator, Dimensional Insight’s advanced ETL (Extract, Transform, Load) software, which integrates data from multiple sources and in multiple formats. Prepared data is then processed by one of two multidimensional engines:
- The Spectre engine accesses large volumes of data in memory using a columnar database (cBase) structure. Each request is compiled and executed in memory for optimum performance.
- The Model engine uses Dimensional Insight’s patented cross-indexing technology to produce a database designed for quick access to summarized information, with the complete underlying detail always available.
A single Diver application can contain multiple Models and/or cBases. Using either engine, Diver is unique in its ability to allow users to dive in any direction they wish without the limitations of preset drill paths or hierarchical constraints found in conventional OLAP tools. Diving is a simple point-and-click operation: No SQL queries, scripting, or programming are required to explore and analyze data. Data management software has never been so versatile.
VIEW EXAMPLE OF EHR INTEGRATION DIAGRAM
Add Spectre to Diver Platform for increased speed and efficiency
Spectre and cBase, Dimensional Insight’s completely re-engineered columnar database technology, give the greatest increase in speed and efficiency to features that are most used by Dimensional Insight power analysts. The most important fundamental change is the new column-oriented, shareable database storage format optimized for query-time calculations instead of build-time calculations. The new design takes advantage of hardware innovations and analysis practices to better handle new user behaviors and queries.
OVERVIEW OF SPECTRE ENGINE
Dimensional Insight’s Spectre engine and cBase, the latest columnar database technology, are designed from the ground up to optimize powerful business intelligence. Whether your business is healthcare, supply chain, goods and services, or something else, the Spectre engine delivers fast, scalable, and manageable business intelligence.
Columnar database design
Spectre uses an in-memory, binary-format columnar database. So, just what is columnar database technology and what makes it so fast?
Typically, a relational database stores fields consecutively in a record, like rows in a table. This is a great design when you want to retrieve all the fields of a record every time the record is accessed. However, business intelligence queries typically need to access only one or a few fields of each record. For these queries, the row-oriented design is not very efficient.
In the self-indexing columnar database design, instead of storing all of the fields for each record together, the records are broken up. The “like” fields for all records, or each column of a table, are stored together in blocks of memory. Now, when you want to perform calculations on the data, such as a SUM, MAX, MIN, COUNT, or AVG, only the relevant columns are accessed, making calculations very fast.
The Spectre design is robust enough for challenging enterprise-level business intelligence analysis and delivers fast performance without taxing resources.
- Database size
Spectre does not maintain separate database indexes so the on-disk size of the columnar cBase is small relative to the data input. Spectre handles large data volumes in a single cBase without limits on file size, column count, or number of dimensions, minimizing maintenance tasks.
Cached dives deliver fast response while avoiding stale results. As an in-memory data engine, Spectre answers most queries without needing to access the hard drive, caches the results for reuse, and eliminates costly disk accesses.
When Spectre loads parts of a cBase into memory, it can share the cBase across multiple Spectre processes. Multiple dives running at the same time for users with different access share this memory, and Spectre processes ensure that each user gets the right results without compromising security.
- Low per-user overhead
Spectre delivers fast user performance with a low idle-connection cost per user to support more simultaneous users without a linear increase in memory and processor usage. User connections are closed when the operation completes, and resources are not devoted to idle user sessions.
Spectre is built for speed, both for calculations and for builds, significantly boosting run-time performance for clients and productivity of IT staff.
- Run-time performance
Spectre engine algorithms optimize run-time performance for some of the most commonly used computations. The Spectre calculation engine compiles formulas into machine code optimized for the processor on which it is running and runs the machine code runs raw. These design optimizations shave off computation processing time making run-time performance extremely fast.
- Build times
When your data input amounts to 500 million – 1 billion rows or more, you need builds to turn around quickly. Spectre does not pre-summarize data, so Spectre build times are small relative to the data input, which all adds up to getting current data available to users quicker and more frequently.
Users need rapid information access and IT needs to make sure it can manage and support user requirements. The Diver Platform with Spectre does both with Workbench for developers and DiveTab to keep your mobile workforce connected on the go.
Dimensional Insight’s global team of business intelligence consultants assist with the design, implementation, and customization of your application. Consulting service plans offer the flexibility to deliver complete turnkey solutions or remote support for your internal IT team or any level of service in between, putting you in control of your application.
- Consolidate data sources
Enterprise-level businesses are seeing an increase in the quantity and diversity of data in varied formats from different platforms and the increased need to combine views. Spectre takes advantage of the latest hardware advances, such as faster core speeds and multiple cores for built-in parallel processing, large amounts of memory, solid state disk (SSD), and advanced compiler technology, to radically boost performance in these environments.
Workbench, an integrated development environment (IDE), helps developers manage the entire back-end process, from data source to portal. Spectre configuration and scripts use a single text-based scripting language, which developers access and edit with the robust Workbench editor. The scripting language is simple and powerful for builds and dives. Workbench speeds development with highlights for important parts of the script, code suggestions, and descriptive help.
- DiveTab client
Powered by Spectre, the DiveTab client is a tablet-based mobile technology for self-service reporting and analysis that drives data-driven decision making and information delivery using dashboards. DiveTab uses the speed of Spectre for rapid and secure access to your data and other resources, such as presentations and documents, from a central location.
William Byers, Chief Technology Officer, healthcare industry
Data Warehousing and Business Intelligence Simplified
Because of its unique design, Diver outperforms other data management software products. Diver’s unique methodology does not require the additional expense of creating a data warehouse or the licensing overhead associated with an underlying database. Because Diver’s Models integrate data from any number of disparate sources, users are able to compare, for example, data collected from transactional systems with information in the data warehouse and legacy data sources or spreadsheets and flat files. Dimensional Insight’s unique data Model and strategic use of in-memory technology explains why Diver users experience consistently fast response times, regardless of underlying data volumes.
Put Diver Platform software to work for you.
- Drill down to additional detail data from any dashboard indicator
- Identify, define, and develop metrics that meet project, departmental, or organizational information requirements.
- Quickly develop and deploy dashboards appropriate to each user’s job role and information requirements
- Download dashboard metrics, charts, and data to MS Excel, PowerPoint, or Adobe PDF documents
Extraction, Transformation, and Loading (ETL) tool provides quick and easy access to a multitude of data sources:
- Transactional databases
- Flat files
- ODBC-compliant databases
- Microsoft Excel spreadsheets
- Wide range of proprietary data formats such as ERP, EHR, and operational systems
Powerful Data Analysis Software
- No SQL queries or scripting required to explore and analyze your data
- Multiple clients: Web-based, standalone, and MS Excel add-ins
- Search, filter, sort, group, and export data from any client
- Dozens of chart types and options help you uncover hidden trends and patterns
- OpenStreetMap, Thunderforest, and Stamen™ supported
- Rich set of built-in functions including string, math, statistical, and logical
Admin and Security
- Flexible authentication options: Own, System, LDAP, and DLCGI
- Data authorization via Access Control Lists
- Multiple security levels and data encryption options
- Access control at the data model or field level