Datameer Provides Business Visualization and Discovery for Hadoop


As volumes of data grow in organizations, so do the number of deployments of Hadoop, and as Hadoop becomes widespread, more organizations demand data analysis, ease of use and visualization of large data sets. In our benchmark research on Hadoop, 88 percent of organizations said analyzing Hadoop data is important, and in our research on business analytics 89 percent said it is important to make it simpler to provide analytics and metrics to all users who need them. As my colleague Mark Smith has noted, Datameer has an ambitious plan to tackle these issues. It aims to provide a single solution in lieu of the common three-step process involving data integration, data warehouse and BI, giving analysts the ability to apply analytics and visualization to find the dynamic “why” behind data rather than just the static “what.”

The Datameer approach places Hadoop at the center of the computing environment rather than looking at it as simply another data source. This, according to company officers, allows Datameer to analyze large, diverse data sets in ways that traditional approaches cannot, which in turn enables end users to answer questions that may have fallen outside of the purview of the standard information architecture. However, Datameer does not offer its software as a replacement for traditional systems but as a complement to them. The company positions its product to analyze interaction data and data relationships to supplement transactional data analysis of which both are key types of big data that need analysis. Of course, given that most companies are not likely to rip and replace years of system investment and user loyalty, this coexistence strategy is a pragmatic one.

Datameer approaches analytics via a spreadsheet environment. This, too, is pragmatic because, as our business analytics benchmark research shows, spreadsheets are the number-one tool used to generate analytics (by 60% of organizations). Datameer provides descriptive analysis and an interactive dialog box for nested joins of large data sets, but the tool moves beyond traditional analysis with its ability to provide analytics for unstructured data. Path and pattern analyses enable discovery of patterns in massive data sets. Relational statistics, including different cluster techniques, allow for data reduction and latent variable groupings. Data parsing technology is a big part of unstructured data analysis, and Datameer provides prebuilt algorithms for social media text analytics and blogs, among other sources. In all, more than 200 prebuilt algorithms come standard in the Datameer tool set. In addition, users can access spreadsheet macros, open APIs to integrate functions and use the Predictive Model Markup Language (PMML) for model exchange.

In Datameer’s latest version 2.0 it has advanced in providing business infographics tool that provides a visualization layer that enables exploratory data analysis (EDA) through a standard library of widgets, including graphs, charts, diagrams, maps and word clouds. Visualization is one of the key areas lacking in big data deployments today. Analysts work in a free-form layout environment with an easy-to-use drag-and-drop paradigm. Datameer’s WYSIWYG editor provides real-time management of the creation and layout of infographics, allowing analysts to see exactly what the end design will look like as they create it. It also now distributes through HTML5, which allows cross-platform delivery to multiple environments. This is particularly important as Datameer is targeting the enterprise environment, and HTML5 provides a low-maintenance “build once, deploy anywhere” model for mobile platforms.

Datameer is an innovative company, but its charter is a big one, given that it is in a competitive environment at multiple levels of the value delivery chain. Its ability to seamlessly integrate analytics and visualization tools on the Hadoop platform is a unique value proposition; at the same time, it will likely need to put more effort into visualization that is available from other data discovery players. All in all, for enterprises looking to take advantage of large-scale data in the near term that don’t want to wait for other vendors to provide integrated tools on top of Hadoop, Datameer is a company to consider.

Regards,

Tony Cosentino – VP & Research Director

2 thoughts on “Datameer Provides Business Visualization and Discovery for Hadoop

  1. […] One of IBM’s answers to the question of the skills gap comes in the form of BigSQL. A newly announced feature of InfoSphere BigInsights 2.1, BigSQL layers on top of BigInsights to provide accessibility through industry-standard SQL and SQL-based applications. Providing access to Hadoop has been a sticking point for organizations, since they have traditionally needed to write procedural code to access Hadoop data. BigSQL is similar in function to Greenplum’s Pivotal, Teradata Aster and Cloudera’s Impala, where SQL is used to mine data out of Hadoop. All of these products aim to provide access for SQL-trained users and for SQL-based applications, which represent the predominance of BI tools currently deployed in industry. The challenge for IBM, with a product portfolio that includes BigInsights and Cognos Insight, is to offer a clear message about what products meet what types of analytic needs for what types of business and IT professional needs. In addition further clarity from IBM on when to use big data analytics software partners like Datameer who was on an industry panel at the event and part of IBM global educational tour that I have also analyzed. […]

  2. […] One of IBM’s answers to the question of the skills gap comes in the form of BigSQL. A newly announced feature of InfoSphere BigInsights 2.1, BigSQL layers on top of BigInsights to provide accessibility through industry-standard SQL and SQL-based applications. Providing access to Hadoop has been a sticking point for organizations, since they have traditionally needed to write procedural code to access Hadoop data. BigSQL is similar in function to Greenplum’s Pivotal, Teradata Aster and Cloudera’s Impala, where SQL is used to mine data out of Hadoop. All of these products aim to provide access for SQL-trained users and for SQL-based applications, which represent the predominance of BI tools currently deployed in industry. The challenge for IBM, with a product portfolio that includes BigInsights and Cognos Insight, is to offer a clear message about what products meet what types of analytic needs for what types of business and IT professional needs. In addition further clarity from IBM on when to use big data analytics software partners like Datameer who was on an industry panel at the event and part of IBM global educational tour that I have also analyzed. […]

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