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I recently attended the 2014 global analyst summit in San Francisco hosted by Pitney Bowes, an old technology company (now in business for 94 years) that has a new focus in its software along with an entirely new executive team. These leaders unveiled a business and technology strategy meant to demonstrate the company’s commitment to software. For many years it has been known mostly for mail services and postage metering, but Pitney Bowes also has made investments in software that can help companies change their business processes by optimizing their information assets. Over the past few years the company has had its ups and downs as regards its corporate mission, as I wrote in 2012. Most of the turmoil was due to conflicting agendas from past management, but other factors were the company was not as clear in communicating the value of its combined software portfolio and not capitalizing on the demand in lines of business and IT for information management and analytics software.

vr_Info_Optimization_10_reasons_to_change_information_availabilityPitney Bowes has several important assets. Its location intelligence software can provide consumers with accurate information about and directions to locations, enable businesses to target customers more accurately and help businesses be more responsive by adding a geographic context to customer information. Pitney Bowes also has advanced its efforts in information management to integrate and enrich data through spatial processing with a specialization in customer informationMy analysis of Spectrum, its information management software suite, found innovation in its support for analytical and operational use. Organizations are changing how they make information available as lines of business and IT share responsibility for improving information availability, which they do in 42 percent of organizations participating in our information optimization research; the most common reasons for doing so are to improve operational efficiency (cited by 67%) and to gain a competitive advantage (63%).

The latest version of the Spectrum Technology Platform includes data enrichment and quality in its data integration offering. It has advanced in search, query design, in-memory caching and support for Hadoop. The platform also is the foundation for a master information hub that can build relationship-based maps that Pitney Bowes calls knowledge graphs. These maps are more powerful than data relationship-based models that can’t map complex relationships and present them visually. In IT domains this is called master data management, but it goes beyond the usual entity relationship modeling to visualize and manage customer information from a business perspective; this can help bring business users into the process. It also can discover the locations of any information, which our information optimization research finds is important to more than one-fifth (22%) of companies. Having consistent information, particularly about customers, is critical for interaction across a business in providing the best possible customer experience. The Spectrum Platform also can process data in real time, which is attractive to the company’s new customers including large retailers and social media companies like Facebook. We find that only one-fourth (26%) of organizations are happy with their current technology used to provide information, which indicates an opportunity for Pitney Bowes to take a more aggressive position in the market.

vr_Customer_Analytics_02_drivers_for_new_customer_analyticsIn addition Pitney Bowes has customer and marketing analytics software called Portrait Analytics, which offers an engaging way to visualize and interact with customer information. It also can predict potential results through the Portrait Miner application. Another product, Portrait Uplift, can help companies can use the analytics to apply adaptive learning from customer interactions to model how customers will interact and where changes might be needed to stimulate purchasing and reduce churn. These applications have significant potential for marketing and other customer-focused functions because they do not require a data scientist to use them. In our next-generation customer analytics research more than half (59%) of participants said it is very important to improve them while only 15 percent are satisfied with their current efforts. Predictive analytics is the type of advanced analytics most important to 69 percent of organizations, and only one-fifth (22%) are happy with their current software. Pitney Bowes is in position to look for opportunities here as long as it focuses its efforts to the top drivers that are improving the customer experience (63%) and improve the customer service strategy (57%).

The company has not lost its focus on location intelligence software. Its flagship product here remains MapInfo, but it has made investments to highlight its potential for enterprise location intelligence by supporting it in social media and Internet location-based services. A series of new releases of MapInfo after the current version 12 are coming in 2014. The company says that enhancements will include the user experience, a more contextual interface, 64-bit processing, a layout designer, contextual menus and display management. To take advantage of multiple-core processing, Pitney Bowes has segmented processes to accelerate performance. Our latest research in location analytics found that reliability, which includes performance and scalability, is the third-most important software evaluation criterion. The updates also will expand mapping from vector-based to grid-based analysis. In addition mobile technology is a priority for MapInfo, as it should be: This is the second-most important technology innovation according to our location analytics research. MapInfo Stratus is a cloud-based extension of MapInfo Pro. Some support for mobile devices is available today, and more improvements to the experience are coming. This and other advances address the innovations that are changing computing and users’ expectations and are critical to keep MapInfo relevant.

vr_LA_location_analytics_delivers_business_valuePitney Bowes built its position in location intelligence on geocoding, integrating data sets across on-premises and cloud systems for access from a range of applications. Pitney Bowes includes 122 countries in its geocoding, and its software can provide multiple levels of accuracy based on what is available in a cascading approach. It also provides reverse geocoding, which helps identify locations through longitude and latitude; this is used by major social media. Pitney Bowes has advanced the capabilities so users can type ahead to find locations in proximity; this is especially critical for mobile application support. The ubiquity of mobile devices and Internet use and the growth of complex event processing and visualization are bringing new opportunities for Pitney Bowes’ geocoding and location processing. Our location analytics research finds that many organizations view current methods as not reliable, taking too many resources and too slow. Using a dedicated approach can deliver business value like improve customer experience (20%) and gain competitive advantage (17%).

vr_LA_dedicated_technology_provides_satisfactionPitney Bowes has announced the release of Spectrum Spatial, a location intelligence platform built on MapInfo. Additionally Spectrum Spatial Analyst is an interactive tool to examine spatial and location attributes of data. The Spectrum Spatial technology and Spectrum Spatial for BI are the basis for Pitney Bowes establishing new partnerships with IBM and SAP. Having location analytics with business intelligence is still rare and has potential to enhance business analysis as found in almost a third (30%) of organizations while using a dedicated approach with GIS and location analytics provides satisfaction in almost half (49%) of organizations.

Our big data research finds that only 16 percent of organizations are using geospatial analysis in big data analytics; we think this is an overlooked opportunity given the value of location in enhancing information assets. Pitney Bowes has focused on providing location intelligence to suppliers of standard RDBMSs and data warehousing, which are only a subset of the big data environment. But the company realizes the importance of big data and has announced expanded support for it in Spectrum to ensure it can rapidly access these new sources. It includes new in-memory support (50%) for SAP HANA and Hadoop (42%), which are the two types of big data support revealed as most important in our research.

vr_Big_Data_Analytics_15_new_technologies_enhance_analyticsOverall Pitney Bowes software combines data management and analytics with its specialization in location to meet today’s need to optimize information in real time to support both consumers and business decision-makers. In the past year it has gained traction with social media companies and other types of businesses through direct approaches. Its main challenges are that its brand is not known for solving these types of problems and that it has not been able to assert its presence through marketing. Our research on buyers and users of software for information management and big data analytics has identified demand for these capabilities; Pitney Bowes should use its own software to better market and sell its products as well as the technology deserves. Its new executives have made the strategy more clear; now it is time for the organization to execute it through more and better marketing to ensure that potential customers consider its products that deliver business insights.

Regards,

Mark Smith

CEO & Chief Research Officer

I had the pleasure of attending Cloudera’s recent analyst summit. Presenters reviewed the work the company has done since its founding six years ago and outlined its plans to use Hadoop to further empower big data technology to support what I call information optimization. Cloudera’s executive team has the co-founders of Hadoop who worked at Facebook, Oracle and Yahoo when they developed and used Hadoop. Last year they brought in CEO Tom Reilly, who led successful organizations at ArcSight, HP and IBM. Cloudera now has more than 500 employees, 800 partners and 40,000 users trained in its commercial version of Hadoop. The Hadoop technology has brought to the market an integration of computing, memory and disk storage; Cloudera has expanded the capabilities of this open source software for its customers through unique extension and commercialization of open source for enterprise use. The importance of big data is undisputed now: For example, our latest research in big data analytics finds it to be very important in 47 percent of organizations. However, we also find that only 14 percent are very satisfied with their use of big data, so there is plenty of room for improvement. How well Cloudera moves forward this year and next will determine its ability to compete in big data over the next five years.

Cloudera’s technology supports what it calls an enterprise data hub (EDH), vr_Big_Data_Analytics_04_types_of_big_data_for_analyticswhich ties together a series of integrated components for big data that include batch processing, analytic SQL, a search engine, machine learning, event stream processing and workload management; this is much like the way relational databases and tools evolved in the past. These features also can deal with the types of big data most often used, according to our research: 40 percent or more use five types, from transactional data (60%) to machine data (42%). Hadoop combines layers of the data and analytics stack from collection, staging and storage to data integration and integration with other technologies. For its part Cloudera has a sophisticated focus on both engineering and customer support. Its goal is to enable enterprise big data management that can connect and integrate with other data and applications from its range of partners. Cloudera also seeks to facilitate converged analytics. One of these partners, Zoomdata, demonstrated the potential of big data analytics in analytic discovery and exploration through its visualization on the Cloudera platform; its integrated and interactive tool can be used by business people as well as professionals in analytics, data management and IT.

Cloudera latest major release with Cloudera Enterprise 5 brought a range of enterprise advancements from in-memory processing, vr_Big_Data_Analytics_11_implementing_analytics_through_hadoopresource management, data management, data protection to name a few. Cloudera offers a range of product options that they announced to make it easier to embrace their Hadoop technology. Cloudera Express is its free version of Hadoop, and it provides three editions licensed through subscription: basic, flex and data hub. The Flex Edition of Cloudera Enterprise has support for analytic SQL, search, machine learning, event stream processing and online NoSQL through the Hadoop components HBase, Impala, Spark and Navigator; a customer organization can have one of these per Hadoop cluster. The Enterprise Data Hub (EDH) Edition enables use of any of the components in any configuration. Cloudera Navigator is a product for managing metadata, discovery and lineage, and in 2014 it will add search, annotation and registration on metadata. Cloudera uses Apache Hive to support SQL through HiveQL, and Cloudera Impala provides a unique interface to the Hadoop file system HDFS using SQL. This is in line with what our research shows organizations prefer: More than half (52%) use standard SQL to access Hadoop. This range of choices in getting to data within Hadoop helps Cloudera’s customers realize a broad range of uses that include predictive customer care, market risk management, customer experience and other areas where very large volumes of information can be applied for applications that were not cost-effective before. With EDH Edition Cloudera can compete directly with large players IBM, Oracle, SAS and Teradata, all of which have ambitions to provide the hub of big data operations for enterprises.

Having open source roots, community is especially important to Hadoop. vr_Big_Data_Analytics_07_dissatisfaction_with_big_data_analyticsPart of building a community is providing training to certify and validate skills. Cloudera has enrolled more than 50,000 professionals in its Cloudera University and works with online learning provider Udacity to increase the number of certified Hadoop users. It also has developed academic relationships to promote Hadoop skills being taught to computer science students. Our research finds that this sort of activity is necessary: The most common challenge in big data analytics processes for two out of three (67%) organizations is not having enough skilled resources; we have found similar issues in the implementation and management of big data. The other aspect of a community is to enlist partners that offer specific capabilities. I am impressed with Cloudera’s range of partners, from OEMs and system integrators to channel resellers such as Cisco, Dell, HP, NetApp and Oracle to support in the cloud from Amazon, IBM, Verizon and others.

To help it keep up Cloudera announced it has raised another $160 million from the likes of T. Rowe Price, Michael Dell Ventures and Google Ventures to add to financing from venture capital firms. With this funding Cloudera outlined its investment focus for 2014 which will concentrate on advancing database and storage, security, in-memory computing and cloud deployment. I believe that it will need to go further to meet the growing needs for integration and analytics and prove that it can provide a high-value integrated offering directly as well as through partners. Investing in its Navigator product also is important, as our research finds that quality and consistency of data is the most challenging aspect of the big data analytics process in 56 percent of organizations. At the same time, Cloudera should focus on optimizing its infrastructure for the four types of data discovery that are required according to our analysis.

Cloudera’s advantage is being the focal point in the Hadoop ecosystem while others are still trying to match its numbers in developers and partners to serve big data needs. Our research finds substantial growth opportunity here: Hadoop will be used in 30 vr_Info_Optimization_12_big_data_is_widely_usedpercent of organizations through 2015 and another 12 percent are planning to evaluate it. Our research also finds a significant lead for Cloudera in Hadoop distributions, but other options like Hortonworks and MapR are growing. The research finds that the most of these organizations are seeking the ability to respond faster to opportunities and threats; to do that they will need to have a next generation of skills to apply to big data projects. Our research in information optimization finds that over half (56%) of organizations are planning to use big data and Hadoop will be a key focus for those efforts. Cloudera has a strong position in the expanding big data market because it focuses on the fundamentals of information management and analytics through Hadoop. But it faces stiff competition from the established providers of RDBMSs and data appliances that are blending Hadoop with their technology as well as from a growing number of providers of commercial versions of Hadoop. Cloudera is well managed and has finances to meet these challenges; now it needs to be able to show many high-value production deployments in 2014 as the center of business’s big data strategies. If you are building a big data strategy with Hadoop, Cloudera must be in the evaluation priority for an organization.

Regards,

Mark Smith

CEO & Chief Research Officer

Mark Smith – Twitter

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