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vr_Big_Data_Analytics_02_defining_big_data_analyticsTeradata continues to expand its information management and analytics technology for big data to meet growing demand. My analysis last year discussed Teradata’s approach to big data in the context of its distributed computing and data architecture. I recently got an update on the company’s strategy and products at the annual Teradata analyst summit. Our big data analytics research finds that a broad approach to big data is wise: Three-quarters of organizations want analytics to access data from all sources and not just one specific to big data. This inclusive approach is what Teradata as designed its architectural and technological approach in managing the access, storage and use of data and analytics.

Teradata has advanced its data warehouse appliance and database technologies to unify in-memory and distributed computing with Hadoop, other databases and NoSQL in one architecture; this enables it to move to center stage of the big data market. Teradata Intelligent Memory provides optimal accessibility to data based on usage characteristics for DBAs, analysts and business users consuming data from Teradata’s Unified Data Architecture (UDA). Teradata also introduced QueryGrid technology, which virtualizes distributed access to and processing of data across many sources, including the Teradata range of appliances, Teradata Aster technology, Hadoop through its SQL-H, other databases including Oracle’s and data sources including the SAS, Perl, Python and even R languages. Teradata can provide push-down processing of getting data and analytics processed through parallel execution in its UDA including data from Hadoop. Teradata QueryGrid data virtualization layer can dynamically access data and compute analytics as needed making it versatile to meet a broadening scope of big data needs.

Teradata has embraced Hadoop through a strategic relationship with Hortonworks. Its commercial distribution, Teradata Open Distribution for Hadoop (TDH) 2.1, and originates from Hortonworks. It recently announced Teradata Portfolio for Hadoop 2, which has many components. There is also a new Teradata Appliance for Hadoop; this is its fourth-generation machine and includes previously integrated and configured software with the hardware and services. Teradata has embraced and integrated Hadoop into its UDA to ensure it is a unified part of its product portfolio that is essential as Hadoop is still maturing and is not ready to operate in a fully managed and scalable environment.

Teradata has enhanced its existing portfolio of workload-specific appliances. It includes the Integrated Big Data Platform 1700, which handles up to 234 petabytes, the Integrated Data Warehouses 2750 for up to 21 petabytes for scalable data warehousing and the 6750 for balanced active data warehousing. Each appliance is configured for enterprise-class needs, works in a multisystem environment and supports balancing and shifting of workloads with high availability and disaster recovery. They are available in a variety of ratios including disks, arrays and nodes, which makes them uniquely focused for enterprise use. The appliances run version 15 of the Teradata database with Teradata Intelligent Memory and interoperate through integrated workload management. In a virtual data warehouse the appliances can provide maximum compute power, capacity and concurrent user potential for heavy work such as connecting to Hadoop and Teradata Aster. UDA enables distributed management and operations of workload-specific platforms to use data assets efficiently. Teradata Unity now is more robust in moving and loading data, and Ecosystem Manager now supports monitoring of Aster and Hadoop systems across the entire range of data managed by Teradata.

Teradata is entering the market for legacy SAP applications with Teradata Analytics for SAP, which provides integration and data models across lines of business to use logical data from SAP applications more efficiently. Teradata acquired this product from a small company in last year; it uses an approach common among data integration technologies today and can make data readily available through new access points to SAP HANA. The product can help organizations that have not committed to SAP and its technology roadmap, which proposes using SAP HANA to streamline processing of data and analytics from business applications such as CRM and ERP. For others that are moving to SAP, Teradata Analytics for SAP can provide interim support for existing SAP applications.

Teradata continues to advance JavaScript Object Notation (JSON) integration for support of document-oriented databases that are schemaless and semistructured. JSON has become a critical tool as more applications need to store and access data efficiently. NoSQL databases have become more popular recently: 25 percent of organizations in our big data analytics research are using them today, 20 percent  plan to use them within two years, and another 23 percent are evaluating NoSQL. With this focus Teradata provides for its customers application and operational support beyond just supporting data for analytic purposes.

Teradata continues expansion of its Aster Discovery Platform to process analytics for discovery and exploration and also advances visualization and interactivity with analytics, which could encroach on partners that provide advanced analytics capabilities like discovery and exploration. Organizations looking for analytic discovery tools should consider this technology overlap. Teradata provides a broad and integrated big data platform and architecture with advanced resource management to process data and analytics efficiently. In addition it provides archiving, auditing and compliance support for enterprises. It can support a range of data refining tasks including fast data landing and staging, lower workload concurrency, and multistructured and file-based data.

Teradata efforts are also supported in what I call a big data or data warehouse as a service and is called Teradata Cloud. Its approach is can operate across and be accessed from a multitenant environment where it makes its portfolio of Teradata, Aster and Hadoop available in what they call cloud compute units. This can be used in a variety of cloud computing approaches including public, private, hybrid and for backup and discovery needs. It has gained brand name customers like BevMo and Netflix who have been public references on their support of Teradata Cloud. Utilizing this cloud computing approach eliminates the need for placing Teradata appliances in the data center while providing maximum value from the technology. Teradata advancements in cloud computing comes at a perfect time where our information optimization research finds that a quarter of organizations now prefer a cloud computing approach with eight percent prefer it to be hosted by a supplier in a specific private cloud approach.

vr_Info_Optimization_10_reasons_to_change_information_availabilityWhat makes Teradata’s direction unique is moving beyond its own appliances to embrace the enterprise architecture and existing data sources; this makes it more inclusive in access than other big data approaches like those from Hadoop providers and in-memory approaches that focus more on themselves than their customers’ actual needs. Data architectures have become more complex with Hadoop, in-memory, NoSQL and appliances all in the mix. Teradata has gathered this broad range of database technology into a unified approach while integrating its products directly with those of other vendors. This inclusive approach is timely as organizations are changing how they make information available, and our information optimization benchmark research finds improving operational efficiency (for 67%) and gaining a competitive advantage (63%) to be the top two reasons for doing that. Teradata’s approach to big data helps broaden data architectures, which will help organizations in the long run. If you have not considered Teradata and its UDA and new QueryGrid technologies for your enterprise architecture, I recommend looking at them.

Regards,

Mark Smith

CEO & Chief Research Officer

vr_SF12_07_impediments_in_sales_motivate_investmentIn an analyst perspective at the beginning of this year I wrote that sales organizations must step beyond conventional wisdom to generate the best outcomes. One such step is to invest in software that delivers immediate value to manage sales and be efficient in its operations. Our latest research on sales organizations finds that inconsistent execution (53%), scattered information (48%) and limited visibility (42%) are motivating investment to improve sales. At CompCloud, its annual conference, Xactly unveiled advances in its software to help improve the effectiveness and productivity of sales organizations. Spokespeople said the company’s sales compensation products have helped users manage US$10 billion in commissions in the past two years.

To make it easier to access critical information from its applications Xactly now supports the range of mobile devices running native Apple iOS, Android and HTML5 apps. The mobile capabilities enable users to view commission statements, track quota attainment and compare performance to team rankings. Xactly is right to advance its mobile efforts as account managers and management extensively use smartphones and tablets. Our latest research in sales finds that smartphones will be deployed to four out of five (81%) in sales and tablets to three-quarters by the end of 2015.

The company also announced the release of Xactly Quota to help management and analysts allocate quota assignments to teams. By automating the quota process and providing visibility into quota performance this application helps reduce manual effort and potential errors in those tasks. The quota management application can link with Xactly Incent to help users plan sales targets and link potential commissions to payments. They can collaborate in designing and agreeing on quotas, and the comments feature enables direct feedback. Our research finds that quota attainment is the top way to measure overall sales performance, so this feature is likely to please Xactly’s customers and increase sales. After aligning quotas and commissions, the next logical advance would be to help users manage sales forecasts to support progress toward quotas and ultimately commissions. Comparing quotas to forecasts is a top priority for sales teams, according to our research. Xactly’s products can integrate forecasts into its analytics, which is a key first step to assess to quota and potential commission. I have already written that dedicated technology enables successful forecasting.

At the conference I got to review demonstrations of its analytics and benchmarks in Xactly Insights that help provide performance metrics from all the data it collects from its customers. Such measures can be useful: Xactly released a report on performance and quotas showing that 79 percent of sales reps selling software as a service miss their quotas. These insights help provide a guideline to where a company can improve in the design of its quotas which Xactly released a new application but also where it compares in the market to others. Xactly has been able to take the aggregate of its own customers’ metrics in using their products to provide some insightful perspective on a range of compensation and time related sales metrics.

Xactly unveiled Xactly Objectives at its 2013 conference that I covered, and we named it the prestigious 2013 Technology VentanaResearch_TechInnovation_Award_Winner_2013Innovation Award winner for sales. Now the product is fully localized to support Spanish, French, German and other languages. It is easy for managers and sales reps to track progress toward their overall objectives. Having a system to identify overarching sales objectives and link them to sales compensation is important to motivate and guide personnel on a regular basis. The Xactly Objectives can be used anywhere in an organization too, which makes it appealing to any department.

Other improvements outlined at this year’s conference included more comprehensive incentive statements, analytics that can be displayed in any HTML5-compliant Web browser, flexibility in plan rules with lookup tablets and adaptations to credit allocations. Xactly continued focus on satisfying its customers through product improvements have provided it a very high customer retention rate.

Xactly continues to focus on inspiring sales management and operations to making sales more productive and generate higher level of sales. Its software is more appropriate for sales compensation and related processes than CRM or SFA applications and much better than using general-purpose spreadsheets. Our research finds that more than half of sales organizations still use spreadsheets for these purpose and that doing this undermines their ability to manage sales with accurate information. In today’s intensely competitive sales environment, Xactly is positioned to grow. Sales organizations that seek to improve these sales and compensation processes and provide the information that sales teams need both to perform well and be satisfied in their jobs should examine Xactly’s software.

Regards,

Mark Smith

CEO and Chief Research Officer

Mark Smith – Twitter

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