IBM Content Analytics adds value to Cognos BI

Transcription

1 IBM Software IBM Industry Solutions IBM Content Analytics adds value to Cognos BI

2 2 IBM Content Analytics adds value to Cognos BI Analyzing unstructured information It is generally accepted that about 80 percent of the information managed by an organization is in an unstructured form. Examples of unstructured information include documents, s, web pages, call center notes, social media, and many more. IBM Content Analytics with Enterprise Search (Content Analytics) is a platform that helps anticipate and shape business outcomes by surfacing new insights from unstructured information, enabling organizations to tackle complex analytics issues even as information grows to big scale. Content Analytics provides a complete set of advanced technologies for analyzing unstructured, including: text analytics, natural language processing, content mining, sentiment analysis, confidence assessment, content classification, visualization and exploration. Line of business users with little or no prior analytics expertise can gain insights from information across multiple structured and unstructured sources using built-in features to identify meaningful concepts and key trends and take action. Structured (the remaining 20 percent of information in an enterprise) is information that is usually represented as fields, such as records in a relational base or rows and columns in a worksheet. IBM Cognos Business Intelligence (Cognos BI) is an integrated business intelligence suite that provides a wide range of functions to help business analysts explore structured and make effective business decisions by analyzing and creating and viewing analytical reports. Structured analytics tools like Cognos BI are typically used to answer business questions surrounding the Who, What, When, and Where. Content Analytics enables the analysis of related unstructured which can uniquely answer business questions surrounding the How and Why. Content Analytics connects to a wide variety of internal and external sources to ingest and then read the information using the same Natural Language Processing (NLP) engine used in the IBM Watson solutions. Content Analytics can determine the meaning of information much like a human would, and then extract that meaning in structured form for additional analytical processing. It can then create Cognos BI reports and export those reports and analytics- enhanced information to sets and models that are further analyzed within Cognos BI. This paper will explore use cases that utilize Content Analytics to integrate business insight from unstructured into Cognos BI, and to enhance the process of fast model development and the value of Cognos BI analytical tools.

3 IBM Software 3 The business value of unstructured information Content Analytics enables the analysis of unstructured, and when this information is combined with related structured, it creates a powerful set of results that are used to answer business questions surrounding the How and Why in your business environment. Let s take the example of a mobile telecommunications operator that has a What question for structured : What is month-to-month customer attrition for a new mobile phone model? If the answer is a 9 percent attrition rate, then a critical next question is why this trend? An analysis of client inbound call transcripts and , hosted and third-party forums, and social media mentions (all unstructured text interactions with customers) indicates the new phone has a poor battery life. This mobile operator is now in a position to take action with their phone supplier to remedy the battery life issue and reduce or eliminate customer attrition. The answers to How and Why are often buried in the meaning and context found in unstructured information, and when surfaced, this insight can be used to take action and improve business performance. As the adoption of big and analytics continues to expand, many organizations are realizing the value they can derive from using a solution like Content Analytics to expand their view of to include all of the information they have, not just the 20 percent typically found in structured form. In February 2013, Aberdeen Group published a research brief titled Content Analytics: Helping the Best-in-Class Drive Superior Customer Service which measured the business results of organizations that added content analytics to their existing structured analytics. As the graphic below shows, those organizations analyzing unstructured information (the green bar) reported a 17 percent year-to-year improvement in the accuracy of their business decisions, versus a 5 percent increase for those not analyzing unstructured information. They also reported a significantly higher quality of analysis. More importantly, as the graphic below shows, the research indicated that analyzing unstructured information lead to significantly improved sales performance, customer satisfaction, customer retention and something called net promoter score a measure of word of mouth, grass roots recommendations. 20% 17% Year over year change n=82 5% 14% 7% 12% 0% Accuracy of business decisions Quality of analysis 2% Time spent on centric processes Analyzing unstructured Not analyzing unstructured Figure 1: Content analytics streamlines business processes Source: Aberdeen Group, January 2013

4 4 IBM Content Analytics adds value to Cognos BI 15% Analyzing unstructured Not analyzing unstructured Year over year change n=82 10% 5% 11% 8% 8% 3% 2% 7% 0% -1% -2% -5% Sales team meeting quota Customer satisfaction Customer retention Net promoter score Figure 2: Content analytics improves customer service Source: Aberdeen Group, January 2013 Connecting structured and unstructured Content Analytics crawls, parses, analyzes and indexes structured and unstructured. It annotates the with information about parts of speech, named entities and relationships, and additional terms, codes, or pieces of information that establish relationships and linkages among documents, rows and columns, within both structured and unstructured sources. From the resulting collection of information, Content Analytics enables the automatic creation of Cognos BI reports that contain the analysis results. The underlying report model, along with analyzed documents and, can also automatically be exported to a Cognos BI relational base (see Figure 3). Content Analytics integration with Cognos BI Cognos BI helps business users understand structured that is represented as fields, such as records in relational base tables. Content Analytics extracts information from unstructured, which is usually in free text format. Because this extracted from text documents can be treated as structured, Cognos BI can consume information from Content Analytics. You can pass information from Content Analytics to Cognos BI in one of two ways: by exporting documents with content analysis results or by creating reports that contain content mining results.

5 IBM Software 5 Exporting documents with Content Analytics results A document and analytics results set can be exported to Cognos BI for additional in-depth analysis of both structured and unstructured, together. By using the export functions of Content Analytics, you can deliver documents into star-schema tables in a relational base. In addition, a Cognos BI model can be created based on the star-schema, and a package for the model can be published automatically. Using the package, users can create reports and perform all types of structured analytical processes (including OLAP) against the exported. A Cognos BI Action Log XML file for the model can also be generated, which enables users to modify and extend the model as required using IBM Cognos Framework Manager. Creating reports with Content Analytics Miner results Content Analytics Miner allows you to explore different facets and analytical views of the analyzed content in a collection. You can also share and extend the use of this information in your business by generating a report that can be opened with Cognos BI. The report is made available on the IBM Cognos BI portal page, which makes the report easy to share among users. When business users view the report, they manage it like any other report, including editing it with Cognos Report Studio. Report users can also drill into the information with Content Analytics Miner by clicking a link provided in the report. This feature allows an analyst to further explore analytic results in support of critical business decisions. Content analytics Ingest Analyzed Structured Unstructured Analytics-enhanced Figure 3: Cognos BI relational base

6 6 IBM Content Analytics adds value to Cognos BI Accelerating the Cognos development cycle Content Analytics can also shorten the time it takes to develop new Cognos BI reports and dashboards. Through the use of the Cognos BI report and model generation capabilities described above, Content Analytics can integrate unstructured insights with structured, and can also be used in scenarios where Cognos BI is analyzing structured only. For example, Content Analytics can be used to aid in shortening the structured analytics process, from mart creation, exploration, OLAP model building, through analyst validation. To accelerate the Cognos BI modeling cycle, Content Analytics uses supported connectors to structured like relational bases, and crawls and indexes the in source rows and columns. It treats the information like an unstructured document and enhances the index with analytic statistics that represent facets or dimensions of the. Once the structured sources are indexed, Content Analytics Miner allows you to easily pivot on any facet or dimension of the information. Models developed in Content Analytics can be exported to Cognos BI in star-schema format (see Figure 4). A Cognos Framework Manager model can also be generated, which can be modified and extended as required. Many organizations will be able to reduce the overall time required to develop new and ad hoc Cognos BI analytics by using Content Analytics to explore, model and report on the information by exporting the model and report directly to Cognos BI. Traditional method Data scientist models various queries to answer business question Creates star scheme base model to represent OLAP cubes Using content analytics Embrace structured Create models quickly from Content Analytics Miner view Export all elements and Figure 4: Cognos BI in star-schema

7 IBM Software 7 Enterprise Search IBM Content Analytics with Enterprise Search, as the name suggests, also contains an enterprise search solution which is used by industry-leading organizations to address complex, cross-enterprise search use cases, and as a platform for unstructured analytics-enhanced search-based applications. IBM Content Analytics contains features that link search and analytics collections together. Using these features, a search user or business analyst can flag documents found during a search query and export those documents to an analytics collection where they can be modeled and related to structured, and the resulting models and reports can be exported to Cognos BI. As you can see, the opportunity to connect search results and unstructured and structured together can deliver a tremendous value to organizations by making information (both structured and unstructured) and insights available to the business professionals who need them to make business decisions. Summary Losing customers is costly, and reacting to complaints is no longer enough to keep them satisfied. Customer service needs to go beyond handling dissatisfied customers and build relationships with customers so they are profitable, loyal advocates. Business analytics can help you transform customer service into a complete customer care center that provides an exceptional experience no matter where customer interaction occurs. The IBM Business Analytics for Customer Service Solution combines predictive analytics, business intelligence and social media analytics techniques to help you gain a comprehensive view of each customer. The result is a positive customer experience that spans channels and occurs at all points of interaction. For more information To learn more about IBM Content Analytics, please contact your IBM marketing representative, or visit the following website: ibm.com/software/ecm/content-analytics

8 Copyright IBM Corporation 2013 IBM Corporation Software Group Route 100 Somers, NY Produced in the United States of America October 2013 IBM, the IBM logo, ibm.com, and Cognos are trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at Copyright and trademark information at This document is current as of the initial date of publication and may be changed by IBM at any time. Not all offerings are available in every country in which IBM operates. THE INFORMATION IN THIS DOCUMENT IS PROVIDED AS IS WITHOUT ANY WARRANTY, EXPRESS OR IMPLIED, INCLUDING WITHOUT ANY WARRANTIES OF MERCHANT- ABILITY, FITNESS FOR A PARTICULAR PURPOSE AND ANY WARRANTY OR CONDITION OF NON-INFRINGEMENT. IBM products are warranted according to the terms and conditions of the agreements under which they are provided. Please Recycle ZZW03275-USEN-00