Big Data Analytics Platform for Modern BI

Self-Service BI for Data That’s Too Big To Move

If your data is too big to move, and you think it’s too hard, too expensive, or too risky to use it for end-user analysis, give Zoomdata a look. Zoomdata meets business users’ demanding requirements for BI on Big Data. With Zoomdata, you can interact with big data using dynamic charts, graphs, maps, and pivot tables with fluidity and clarity you simply won’t see anywhere else.

Learn why the cost of keeping data is less than the cost of throwing it away in our Master Class: The Economic Impact of Big Data

Big Data Broke Business Intelligence

Rethink What’s Possible and Practical with Big Data

You can bring big data analytics to casual business users. Zoomdata customers find us when their familiar big data analytics and BI tools fail to deliver on modern data.

Compare how traditional BI and Zoomdata work with big data. Learn why Zoomdata excels where traditional BI fails.
  Traditional BI
Zoomdata
  Full or single stack BI designed for structured data, typically less than a few billion rows. Best of breed data visualization platform designed for big, real-time, and other modern data sources.
General attitude towards big data

Off-load work from the cluster.

Leverage the database cluster.

General user flow Experts develop reports and dashboards for others to consume.

General business users explore data on their own and can share the results with others.

Query engine approach

Pull large amounts of data into a proprietary in-memory data engine for processing. Basic, batch-level direct queries are sometimes offered.

Push down all queries and almost all processing to the database. Supplement with intelligent post-processing when needed. Adaptive and multi-level caching is optional and effective.
Securing and managing big data for BI

Duplicate, secure, manage, and periodically refresh big data extracts in a proprietary middle tier.

Secure and manage big data in scalable, high-performing data platform(s).

Managing large queries

An administrator must reduce the queryable data size by rolling up (aggregating), sampling, and eliminating columns derivative data extract.

Zoomdata optimizes direct queries, applies intelligent caching, and streams query results to the end user.

Scalability

Allocate RAM and other resources to the proprietary middle-tier components.

Allocate RAM and other resources to the database cluster and take advantage of elastic computing capabilities.
User experience with long-running queries

Batch-style query-and-wait: visualizations load after the full query is done, which could significantly delay exploration and discovery.

Data Sharpening streams estimated results within seconds and sharpens the picture so users can interact and explore data while it loads.

Connectivity

Basic JDBC/ODBC connectivity with SQL.

Smart Data Connectors work with native database APIs and query languages, plus SQL for optimum performance, functionality, and interactivity.

Data blending / query federation

Combining large amounts of detailed data requires a tremendous amount of memory and is not always practical.

Multisource Many Ways™ includes the ability to explore relationships between data sources without joins.
Data refresh

Full-on requery (F5).

Optional Live Mode pushes incremental updates to users’ dashboards as frequently as once per second.

Embeddability

Embedded capabilities range from very good to none at all.

JavaScript APIs for web developers, RESTful data and management APIs for app developers, plus iFrame snippets for easy embedding.

 

Bringing big data analytic power to the people

FAQs for Big Data Analytics

A: When exploring big data in Hadoop, you need a high-performing query engine capable of processing data in-place, such as Apache Impala. Zoomdata leverages cluster computing resources like Impala’s fast, parallel processing engine directly on source data.

A: Connecting is the easy part. Traditional BI tools are optimized to periodically copy data into their own proprietary data engines, where it is often transformed and must be separately secured and managed. When traditional BI offers direct connect, you have to wait for long-running queries to finish before you can interact with the data. Zoomdata Data Sharpening™ allows users to explore data while it loads, and since there’s no secondary data tier to manage and secure, the data is inherently safer and the whole data environment is simpler and easier to manage.

A: When data freshness is important but data does not need to be real-time, you can use Zoomdata’s adaptive, multi-level caching so the results of recent queries can be reused and repurposed. Zoomdata is optimized to work particularly fast with data that is partitioned by date, and we provide many ways to prevent unintended full table scans. As data grows bigger and demand for it increases, adding additional computing nodes to the cluster is often cheaper than off-loading subsets of data to secondary systems.

A: While every vendor claims ease-of-use, Zoomdata makes it exceptionally easy for non-technical users to directly explore data on their own, without IT intervention or pre-built, complex models or cubes. Zoomdata is also the only big data visualization platform we know of that covers all three V’s of big data with ease: volume, velocity, and variety.

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Big Data Analytics Platform for Modern BI

If your data is too big to move, check out Zoomdata's big data analytics platform for end-user data discovery and analysis.

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Sales: +1 888-564-4965