Tuesday Mar 05, 2013

Reducing Hadoop TCO

I've been to a number of big data trade shows over the last year, and without fail I have the same conversation with many different people. It goes something like this.

 We discuss Oracle's Big Data Platform and I mention the Big Data Appliance (BDA). "Oh, yes" they say. "That's a great looking machine, but we can build a Hadoop cluster much cheaper than that, so we're not interested." 

 The first thing I do is ask them what kind of cluster they are building. They always say something like "I can get 40 $5K servers in a rack for $200K".

"But that's not an equivalent cluster," I will say. The most important number in Hadoop clusters is the amount of storage. When was the last time you heard somebody talk about a 400 core Hadoop cluster? They always say how many terabytes (or even petabytes) their cluster can store. Those smaller servers often only have a few TB of storage, compared with 36TB on each BDA node. So we quickly establish that their equivalent cluster is no such thing. Often it would actually take 2 or 3 such racks to match the capacity of the Big Data Appliance and their "equivalent" system is much more expensive than they thought.

But it's not just about buying servers. When you buy an engineered system you're also getting the rack, the cables, the switches, pre-installed software, tuning, optimization, integrated support and so on. Add those into the picture, and the Big Data Appliance is much lower cost.  Take a look at this ESG white paper that goes through all the numbers in detail. Here's the key segment from the executive summary:

"Based on ESG's modeling of a medium-sized Hadoop-oriented big data project, the preconfigured Oracle Big Data Appliance is 39% less costly than a “build” equivalent do-it-yourself infrastructure. And using Oracle Big Data Appliance will cut the project length by about one-third."

If you're building a Hadoop cluster, or looking to expand an existing one, you should keep Oracle Big Data Appliance on your shortlist and give it a closer look. 

Thursday Feb 21, 2013

Breakthrough Strategies for HR Success

Aberdeen Group’s recent  study “The HR Executive‘s Agenda” shows organizations using workforce analytics experienced a 14% year-over-year improvement in revenue per employee compared to just 5% for those companies that did not.  Is your organization using analytics  to effectively manage its employees and improve performance?  We often hear from organizations that the key drivers for adopting an analytics-based approach to HR include:

  • Lack of accurate view of workforce profile
  • Measuring the effectiveness of HR
  • Aligning talent management with corporate strategies
  • Understanding the voice and sentiment of the workforce from topics and themes hidden in unstructured content

Join us on for a Webcast to find out how Oracle Business Analytics helps organizations of any size meet key HR challenges and  gain a 360-degree view of critical HR information within the enterprise and beyond.

Event Date: Thursday, February 28, 2013

Event Time: 10 a.m. PT/1 p.m. ET

Register Now 

Monday Feb 11, 2013

You’ve never seen a BI solution with an ROI like this!

"BI helps you make better decisions.” That’s how the value of BI is often described. But is that good enough to justify a substantial investment in BI solutions? Certainly not! What customers are looking for is tangible proof that BI solutions help improve business processes, cut down costs, increase revenue and profitably. To demonstrate the quantitative and qualitative benefits of Oracle Business Intelligence Applications, Oracle recently commissioned Forrester Consulting to conduct a study to determine the Total Economic Impact of Oracle BI Applications.

Oracle BI Applications drastically reduces the time it takes to deploy BI by delivering pre-built analytics for ERP and CRM systems. Oracle's ERP Analytics, help front line managers improve cash flow, control expenses, manage headcount and employee performance, stream-line spend and supply chain operations, and track the financial performance of major projects. Oracle's CRM Analytics provides fact-based insight into the entire sales process and into product demand, customer price sensitivity, and overall pricing. Lastly, Oracle’s Industry Analytics enables businesses take advantage of industry specific analytics to streamline their operations, offer better services, and increase profit margins

A total of four interviews were conducted for this study, involving representatives from the following companies: a power management company, a plumbing hardware company, a software company, and a US city school district system.

The study found that the companies realized the following key benefits*:

Significant ROI** – experienced a three-year risk adjusted return on investment of 97 percent with a 20-month payback period;

Lower procurement spend – realized five percent lower procurement costs in the first year and increased to seven percent in the second year;

Accounts payable savings – achieved savings of more than $1 million per year by the third year;

Lower inventory working capital – experienced 15 percent reduction in inventory for the affected product categories over three years;

Increased gross sales and prices – increased gross sales by 0.4 percent in affected parts of the organization and increased average sales price by 0.3 percent over three years.

IT and business labor savings – achieved efficiencies in both the IT and business sides of the organization;

To learn more about the findings of the study, download a copy of the study here or watch the replay of The Total Economic Impact of Oracle Business Applications Webcast here.

* Source: “The Total Economic Impact of Oracle Business Intelligence Applications," a study conducted by Forrester Consulting on behalf of Oracle, October 2012.

** Composite organization achieved this return.

Thursday Jan 31, 2013

Using In-Database Analytics to Predict Fraud

Your data warehouse stores critical data telling you what is happening in your business and sometimes why it’s happening. But you can go beyond understanding why something went wrong. You can use past data to predict the future, correcting problems before they happen. In a recent survey that Oracle did of over 300 C level executives, 93% of them thought that their companies were losing an average of 14% of their total revenue because they couldn’t fully leverage the information they had already collected. One key way to do this (and you’ll hear more about this in a future survey) is to use predictive analytics. Let’s take a quick look at why and how.

Turkcell is a leading mobile phone provider in Turkey, with over 34 million subscribers. And like most mobile providers a majority of those subscribers use pre-paid accounts and pre-paid cards. Money launderers take advantage of this, and losses for this business are of the order of $5 for every $10,000. This may not seem like much, but with billions of transactions, this adds up to millions of dollars a year.

Like other companies, Turkcell examine huge quantities of data and build models that help it identify and ultimately predict and prevent fraudulent transactions.  Unlike many other companies, Turkcell does this analysis in its data warehouse. With 100 TB of compressed data – representing over a petabyte uncompressed – it would take a long time to move that data out of the warehouse and keep it up to date as new data arrived. And the window to stop the next fraudulent transaction might have already closed.

Oracle Advanced Analytics enables you to perform sophisticated predictive analytics inside a data warehouse. You can mine your data directly while it is inside the Oracle Database using either SQL or R language APIs or the Oracle Data Miner SQL Developer “work flow” GUI extension, depending on your need and existing skills. You build models for past behavior and use that to predict future behavior, improving your accuracy with time. And best of all, there’s no need to move the data around which takes time you might not have and also leaves you exposed to security risks. As Turkcell said “...we can analyze large volumes of customer data and call-data records easier and faster than with any other tool”

Tuesday Jan 15, 2013

Transforming Workforce Management with Oracle Endeca Information Discovery

Human Resources is back in the spotlight.  According to industry benchmarks, the cost of replacing an employee can equate to 1.5-4x an employee’s salary, and given ever shrinking budgets, improving employee retention is viewed as a major way to reduce costs on the bottom line.  In fact, according to a recent study by the Society of Human Resource Management, the three biggest challenges facing HR executives over the next 10 years are retaining and rewarding the best employees (59%), developing the next generation of corporate leaders (52%), and creating a corporate culture that attracts the best employees to organizations (36%).

Fortunately, data abounds which can help organizations make the best decisions necessary to solve these challenges.  Unfortunately, much of the information and the resulting insights which can come from it are outside the reach of traditional business analytics systems, in external websites, social media, text from human resource transactions kept in legacy systems, and documents in content management systems.  With this ever-growing complexity, HR executives can gain competitive advantage through richer intelligence, if they are able to draw new and innovative insight with a tool which provides previously untapped actionable information—Oracle Endeca Information Discovery.

Oracle Endeca Information Discovery helps human resource organizations to improve the relationship between companies and their employees, get to the real root causes behind issues, and create new best practices through a better understanding of the workforce by solving the problems associated with analyzing unstructured data. Oracle Endeca Information Discovery creates transformative opportunities for the business, and enables IT to cost-effectively support them in:  

  • Understanding the voice and sentiment of the workforce.  By providing the ability to use natural-language queries to derive insights from information from all sources, Oracle Endeca Information Discovery provides insight into the effectiveness of strategic and tactical HR decisions such as career changes, organizational realignment, compensation adjustments, training and a host of other significant HR events.
  • Identifying the root causes behind events and exceptions.  By combining structured and unstructured data about the workforce from internal and external sources, HR organizations are empowered to determine the reasons why things happen and respond to findings without direct IT involvement, saving time and cost.
  • Supercharging existing business analytics investments.  With the unscripted exploration of workforce data and full-featured search, navigation & interactive analytics, HR organizations can leverage, improve, and extend existing investments in workforce analytics and HCM applications.
To find out more about Oracle Endeca Information Discovery for workforce, join us at our upcoming webcast on January 29, 2013.  Click here to find out more (http://www.oracle.com/goto/workforceanalytics)

Friday May 18, 2012

The Art of the Possible with Business Analytics

It has been established beyond doubt that data and its analysis can have a huge impact on an organization’s top line and bottom line. Business Analytics helps organizations deliver better business performance in two ways – by optimizing business processes and by helping to innovate. Optimization helps organizations be efficient and effective by taking inefficiencies out of the business processes and focusing on the high impact opportunities. Innovation on the other hand helps organizations by uncovering new customer segments, new product categories, new markets, new business models etc.

The styles of analyzing data are many fold from answering questions like “what is going on?” to “why are the things the way they are?” to “what will happen if I do X or Y?” to “what does the future look like?” Broadly speaking the styles of analytics can be classified into three categories:

·         Exploratory Analysis: The objective of exploratory or investigative analysis is exploration and analysis of complex and varied data – whether structured or unstructured for information discovery.  This style of analysis is particularly useful when the questions aren’t well formed or the value and shape of the data isn’t well understood.

·         Descriptive Analytics: The objective of this style of analysis is to answer historical or current questions like what is going on. why are the things the way they are?. This is the most common style of analysis and here the questions as well as the value and shape of data are well understood.

·         Predictive Analysis: Predictive analysis aims at painting a picture of the future with some reasonable certainty.

So, what’s art of possible with business analytics? It’s the application of the above three styles of analytics to a business scenario for better insights, decisions and results. Let’s try and explain this with an example. Consider this scenario:

You are a Financial Services firm e.g. a large bank and are trying to improve profitability. You read Larry Seldon’s book titled “Angel Customers and Demon Customers” and agree with the findings that 20% of your top customers bring in 80% of the profits and would like to manage you business as a portfolio of customers as opposed to portfolio of products. So, how do you do that? The answer is business analytics.

You can start by using descriptive analytics techniques like operational reports, ad-hoc query, dashboards etc. on data collected from different sources like sales, customer service etc. to determine the profitability of each customer. You can then use predictive analysis techniques like data mining, statistical analysis to further enrich your customer data into profitability segments like high, medium, low and loss making customers. Finally, you can choose different customer service channels like personal banker, phone or ATM to cost effectively serve you customers e.g. a high profitability customer can be served by a personal banker free of charge but if the loss making customer wants a personal banker there will be a charge. Once you have implemented such programs you can use exploratory analysis to gauge the sentiment across social media channels like Facebook and Twitter to see if the programs are working as desired. Better yet you may come up with new innovative business models like mobile banking or online only banking to improve profitability.

That’s the art of possible powered by business analytics. Stay tuned, I intend to publish more examples from different industries to show the art of possible with business analytics.

Wednesday May 02, 2012

Analytics And Agility – Why It Is So Important Today

No question that many IT professionals are feeling the pressure to rapidly deliver analytic solutions that respond to the continuous demands of the business user. Primary research shows that analytics in the context of Big Data continues to be top of mind for executive teams at global enterprises. Executives clearly understand the value of Big Data and analytics and many are very vocal proponents of the value it can bring to bear on the business. What executive is not interested in understanding sales trends, KPI’s, social sentiment about the business and critical metrics, even predictive views of the business?

All these requirements and many more have created a tremendous backlog of analytic application requests. This backlog grows significantly as IT professionals are successful in delivering highly tuned internal analytic solutions that quickly deliver value. Everyone begins to say “I want one of those”!

We are no longer operating in the past when these analytic projects took years to complete and where a “boil the ocean” approach was the norm. Today, we see a changing landscape where Agility is what matters most when it comes to delivering rapid returns on key Big Data and analytic investments. In fact, just about every IT professional is pursuing the Agile model for development where product development efforts of the past are streamlined using methodologies that lean towards delivering high value features that are delivered in short bursts of time. This is clearly the method that is emerging when it comes to rapidly delivering analytic solutions to the end user in short bursts of time where value is immediately evident.

Agility in analytics doesn’t require that the product be a desktop business intelligence solution delivered in silos. In fact, Agile analytics requires that IT and the business users work collaboratively and quickly to ensure strong IT governance while also providing powerful analytic solutions to the end user rather than having the user take on the whole effort.

New Information Discovery solutions such as Oracle Endeca Information Discovery clearly have embraced the notion of delivering high value agile analytic applications in short bursts of time. Some including situational analytic apps.  We have seen this play out frequently where POC’s (proof of concepts) quickly go into production in a very short period of time because of the compelling value that was delivered in the POC.

Agility also means developing in short product iterations, this enables one to deliver an analytic application, get immediate feedback from end-users and rapidly iterate to deliver new or expanded requirements that deliver further value. We are talking weeks not many months. Some projects have gone from 8 week iterations down to 2 week iterations. Because Agile analytic solutions are typically delivered through a browser in a private or public cloud, versus a silo desktop only tool, the new enhancements are readily available for test and validation by the end user. This capability combined with agility also gives the analytic application developer a chance to quickly show that they are meeting the key requirements of the end user.

With increased agility and business user success, we will eventually turn the corner and agility will be the new norm in analytics.

New Oracle Endeca Information Discovery YouTube Channel

The Oracle Endeca Information Discovery Product Management team has been busy building a new YouTube Channel to showcase the capabilities of the Endeca Information Discovery product. The team has started to release a new screencast series for "Getting Started With Endeca Information Discovery. This series will help showcase the strong capabilities of the product. It will also give you a sense of what the business user experience is like and also show you how innovative this solution is for building highly interactive, search driven analytics applications on a variety of data including structured, multi-structured and unstructured data, especially on Big Data. 

We encourage you to check it out at http://www.youtube.com/user/OracleEID/

Monday Apr 09, 2012

Polyglot Analytics

Just like polyglot persistence, where a variety of data stores exist to handle a wide variety of data persistency requirements for different data management use cases, we are now seeing the emergence of a variety of BI and analytic solutions for delivering insight on all types of data. In the context of polyglot persistence, Oracle not only offers the number one relational database solution in the market today, we also deliver market leading NoSQL and In-Memory (TimesTen) as well as our Essbase OLAP engine where they serve as excellent solutions for handling a variety of persistency requirements. Of course, we've had a strong track record of also delivering enterprise class business intelligence and reporting solutions to the market and now have extended the BI and Analytics offering with Oracle Endeca Information Discovery, a data discovery solution that enables one to quickly explore all relevant data whether structured, semi-structured or unstructured in nature. And just like polyglot persistence solutions that compliment one another, we also see the same case for polyglot analytics. Our Business Intelligence solutions complement each other. In fact, they solve different problems and create different kinds of value. Why Polyglot Analytics exist. In a sense, its no different than programmers using different language to tackle different requirements and use cases. As an example, it would not be unusual for server side code to be written in Java while a web page is driven by Javascript or even Ruby. 

Business Intelligence clearly provides proven answers to known questions while out extensions, in this case, Data Discovery, it provides fast answers to new questions formulated by the business user. For example, when the business intelligence report says that warranty claims on the top-selling product went up 15% last month, the new questions are “What changed? What’s the root cause? What are customers saying about this? That exploration happens in a discovery app.

And the relationship goes both ways. Data Discovery creates new KPIs for the BI stack to deliver. For example, a consumer packaged goods company learned that preference for seemingly unrelated brands was highly correlated in certain customer segments. This came from a social media discovery app and suggested new KPIs they quickly pulled into their operational BI system.

Far from replacing their BI systems with data discovery, our customers have instead been able to get far MORE value out of their existing BI systems because they are able to re-focus them on solving the problems they are most effective for, and creating new practices around data discovery to get fast answers to new questions.

Just like NoSQL solutions solve different problems than relational databases, Data Discovery solves new problems that are different than traditional business intelligence and reporting:

The fact that data is available immediately creates demand for it. As more application, consumer, sensor, and mobile data is available to the business, the more the business wants to use that varied data for daily decisions that today get made on intuition and opinion.
In analytics, big variety is a bigger problem than big volume because it can’t be solved by more processing power alone. In addition, the cost and time required to combine diverse data together must come down.
The people making these decisions are experts in the business, not in writing SQL queries. They need a user experience that’s simple to learn and use and this is a core capability of Oracle Endeca Information Discovery. 

It combines structured and unstructured data from inside or outside the company. An enterprise solution must work with the full range of data that matters to an enterprise, including multiple structured sources with diverse schemas, like the vehicle warehouse and quality touch point application data; including unstructured data like the long-form text descriptions in the warranty claims; regardless of whether the data is inside the company, like the warehouse, or outside the company like the NHTSA claims or JD Power data.
It delivers in-memory performance, but is not memory bound. An enterprise solution must maintain fully interactive query response times even when the data is too big to fit in memory. Endeca realized this years ago when it combined search and browsing in eCommerce because search indices are often too big to fit in memory. Oracle EID is written for multi-core, multi-processor servers and uses proprietary optimization algorithms to exploit the full memory hierarchy from on-CPU cache all the way down to disk.  It is a solution for provisioning targeted discovery apps. It provides IT with a new capability to quickly deliver discovery apps wherever the business needs them. 

Over time, we will see strong adoption of Data Discovery applications that further compliment and augment Business Intelligence solutions and why we will continue to see polyglot analytics take hold. 

Friday Apr 06, 2012

Does your analytic solution tell you what questions to ask?

Analytic solutions exist to answer business questions. Conventional wisdom holds that if you can answer business questions quickly and accurately, you can take better business decisions and therefore achieve better business results and outperform the competition. Most business questions are well understood (read structured) so they are relatively easy to ask and answer. Questions like what were the revenues, cost of goods sold, margins, which regions and products outperformed/underperformed are relatively well understood and as a result most analytics solutions are well equipped to answer such questions.
Things get really interesting when you are looking for answers but you don’t know what questions to ask in the first place? That’s like an explorer looking to make new discoveries by exploration. An example of this scenario is the Center of Disease Control (CDC) in United States trying to find the vaccine for the latest strand of the swine flu virus. The researchers at CDC may try hundreds of options before finally discovering the vaccine. The exploration process is inherently messy and complex. The process is fraught with false starts, one question or a hunch leading to another and the final result may look entirely different from what was envisioned in the beginning. Speed and flexibility is the key; speed so the hundreds of possible options can be explored quickly and flexibility because almost everything about the problem, solutions and the process is unknown. 
Come to think of it, most organizations operate in an increasingly unknown or uncertain environment. Business Leaders have to take decisions based on a largely unknown view of the future. And since the value proposition of analytic solutions is to help the business leaders take better business decisions, for best results, consider adding information exploration and discovery capabilities to your analytic solution. Such exploratory analysis capabilities will help the business leaders perform even better by empowering them to refine their hunches, ask better questions and take better decisions. That’s your analytic system not only answering the questions but also suggesting what questions to ask in the first place.
Today, most leading analytic software vendors offer exploratory analysis products as part of their analytic solutions offerings. So, what characteristics should be top of mind while evaluating the various solutions? The answer is quite simply the same characteristics that are essential for exploration and analysis – speed & flexibility. Speed is required because the system inherently has to be agile to handle hundreds of different scenarios with large volumes of data across large user populations. Exploration happens at the speed of thought so make sure that you system is capable of operating at speed of thought. Flexibility is required because the exploration process from start to finish is full of unknowns; unknown questions, answers and hunches. So, make sure that the system is capable of managing and exploring all relevant data – structured or unstructured like databases, enterprise applications, tweets, social media updates, documents, texts, emails etc. and provides flexible Google like user interface to quickly explore all relevant data.
Getting Started
You can help business leaders become “Decision Masters” by augmenting your analytic solution with information discovery capabilities. For best results make sure that the solution you choose is enterprise class and allows advanced, yet intuitive, exploration and analysis of complex and varied data including structured, semi-structured and unstructured data.  You can learn more about Oracle’s exploratory analysis solutions by clicking here.

Friday Mar 30, 2012

Curious About Oracle's BI and Analytics Strategy?

Normally we use this blog space for discussing our business intelligence and analytic efforts along with our views and perspective on this very fast growing marketplace. However, I can't resist mentioning that we are having a great webcast coming up next week, so please do join Oracle's Mark Hurd and Balaji Yelamanchili as they unveil the latest advances in Oracle's strategy for placing analytics into the hands of every one of your decision makers-so that they can see more, think smarter, and act faster. Register now at http://bit.ly/HpAOJk for the Webcast and Live Chat: Wednesday, April 4, 2012 at 9 a.m. PT, 12 p.m. ET, 10 a.m. GMT.  You don't want to miss this event and thank you very much. 

Consumer Oriented Search In Oracle Endeca Information Discovery - Part 2

As discussed in my last blog posting on this topic, Information Discovery, a core capability of the Oracle Endeca Information Discovery solution enables businesses to search, discover and navigate through a wide variety of big data including structured, unstructured and semi-structured data. With search as a core advanced capabilities of our product it is important to understand some of the key differences and capabilities in the underlying data store of Oracle Endeca Information Discovery and that is our Endeca Server. In the last post on this subject, we talked about Exploratory Search capabilities along with support for cascading relevance. Additional search capabilities in the Endeca Server, which differentiate from simple keyword based "search boxes" in other Information Discovery products also include:

The Endeca Server Supports Set Search. 
The Endeca Server is organized around set retrieval, which means that it looks at groups of results (all the documents that match a search), as well as the relationship of each individual result to the set. Other approaches only compute the relevance of a document by comparing the document to the search query – not by comparing the document to all the others. For example, a search for “U.S.” in another approach might match to the title of a document and get a high ranking. But what if it were a collection of government documents in which “U.S.” appeared in many titles, making that clue less meaningful? A set analysis would reveal this and be used to adjust relevance accordingly.

The Endeca Server Supports Second-Order Relvance.
Unlike simple search interfaces in traditional BI tools, which provide limited relevance ranking, such as a list of results based on key word matching, Endeca enables users to determine the most salient terms to divide up the result. Determining this second-order relevance is the key to providing effective guidance.

Support for Queries and Filters.
Search is the most common query type, but hardly complete, and users need to express a wide range of queries. Oracle Endeca Information Discovery also includes navigation, interactive visualizations, analytics, range filters, geospatial filters, and other query types that are more commonly associated with BI tools. Unlike other approaches, these queries operate across structured, semi-structured and unstructured content stored in the Endeca Server. Furthermore, this set is easily extensible because the core engine allows for pluggable features to be added.
Like a search engine, queries are answered with a results list, ranked to put the most likely matches first. Unlike “black box” relevance solutions, which generalize one strategy for everyone, we believe that optimal relevance strategies vary across domains. Therefore, it provides line-of-business owners with a set of relevance modules that let them tune the best results based on their content.
The Endeca Server query result sets are summarized, which gives users guidance on how to refine and explore further. Summaries include Guided Navigation® (a form of faceted search), maps, charts, graphs, tag clouds, concept clusters, and clarification dialogs. Users don’t explicitly ask for these summaries; Oracle Endeca Information Discovery analytic applications provide the right ones, based on configurable controls and rules. For example, the analytic application might guide a procurement agent filtering for in-stock parts by visualizing the results on a map and calculating their average fulfillment time. Furthermore, the user can interact with summaries and filters without resorting to writing complex SQL queries. The user can simply just click to add filters. Within Oracle Endeca Information Discovery, all parts of the summaries are clickable and searchable.

We are living in a search driven society where business users really seem to enjoy entering information into a search box. We do this everyday as consumers and therefore, we have gotten used to looking for that box. However, the key to getting the right results is to guide that user in a way that provides additional Discovery, beyond what they may have anticipated. This is why these important and advanced features of search inside the Endeca Server have been so important. They have helped to guide our great customers to success. 

Friday Mar 16, 2012

Consumer Oriented Search In Oracle Endeca Information Discovery – Part 1

Information Discovery, a core capability of Oracle Endeca Information Discovery, enables business users to rapidly search, discover and navigate through a wide variety of big data including structured, unstructured and semi-structured data. One of the key capabilities, among many, that differentiate our solution from others in the Information Discovery market is our deep support for search across this growing amount of varied big data. Our method and approach is very different than classic simple keyword search that is found in may information discovery solutions. In this first part of a series on the topic of search, I will walk you through many of the key capabilities that go beyond the simple search box that you might experience in products where search was clearly an afterthought or attempt to catch up to our core capabilities in this area. Lets explore.

The core data management solution of Oracle Endeca Information Discovery is the Endeca Server, a hybrid search-analytical database that his highly scalable and column-oriented in nature. We will talk in more technical detail about the capabilities of the Endeca Server in future blog posts as this post is intended to give you a feel for the deep search capabilities that are an integral part of the Endeca Server.

The Endeca Server provides best-of-breed search features aw well as a new class of features that are the first to be designed around the requirement to bridge structured, semi-structured and unstructured big data. Some of the key features of search include type a heads, automatic alphanumeric spell corrections, positional search, Booleans, wildcarding, natural language, and category search and query classification dialogs. This is just a subset of the advanced search capabilities found in Oracle Endeca Information Discovery.

Search is an important feature that makes it possible for business users to explore on the diverse data sets the Endeca Server can hold at any one time. The search capabilities in the Endeca server differ from other Information Discovery products with simple “search boxes” in the following ways:

The Endeca Server Supports Exploratory Search

Enterprise data frequently requires the user to explore content through an ad hoc dialog, with guidance that helps them succeed. This has implications for how to design search features. Traditional search doesn’t assume a dialog, and so it uses relevance ranking to get its best guess to the top of the results list. It calculates many relevance factors for each query, like word frequency, distance, and meaning, and then reduces those many factors to a single score based on a proprietary “black box” formula. But how can a business users, searching, act on the information that the document is say only 38.1% relevant? In contrast, exploratory search gives users the opportunity to clarify what is relevant to them through refinements and summaries. This approach has received consumer endorsement through popular ecommerce sites where guided navigation across a broad range of products has helped consumers better discover choices that meet their, sometimes undetermined requirements. This same model exists in Oracle Endeca Information Discovery. In fact, the Endeca Server powers many of the most popular e-commerce sites in the world.

The Endeca Server Supports Cascading Relevance.

Traditional approaches of search reduce many relevance weights to a single score. This means that if a result with a good title match gets a similar score to one with an exact phrase match, they’ll appear next to each other in a list. But a user can’t deduce from their score why each got it’s ranking, even though that information could be valuable. Oracle Endeca Information Discovery takes a different approach. The Endeca Server stratifies results by a primary relevance strategy, and then breaks ties within a strata by ordering them with a secondary strategy, and so on. Application managers get the explicit means to compose these strategies based on their knowledge of their own domain. This approach gives both business users and managers a deterministic way to set and understand relevance.

Now that you have an understanding of two of the core search capabilities in Oracle Endeca Information Discovery, our next blog post on this topic will discuss more advanced features including set search, second-order relevance as well as an understanding of faceted search mechanisms that include queries and filters.


Saturday Feb 25, 2012

Driving Analytic Advantage

Digital data volumes are increasing tenfold every five years, yet more than 31% of executives say they are not getting the information they need to make important decisions, and 36% say their business units and functional operations are making decisions based on inconsistent information. The resulting “analysis paralysis” is costing the US economy alone over $900 billion per year according to one recent study. Many organizations are turning these challenges into competitive advantage. What are the issues and how can analytics help provide a competitive edge, and drive continuous performance improvement?

Challenges in Managing Business Performance

There are a number of fault lines that interrupt the continuous flow of business processes in the enterprise. The primary focus of ERP, HCM and CRM systems has been to simplify and standardize operational processes. These systems have been very successful over the years but in parallel, analytic systems have been developed to enable you to analyze past performance in areas such as marketing effectiveness, workforce dynamics and customer profitability. Since transaction and analytic systems were created separately, your ability to connect the dots between operational variances and root causes has been elusive.

Furthermore, planning processes have been detached from both operations and analysis. This discontinuity makes it difficult, even impossible for you to achieve a dynamic planning environment where strategic plans cascade to operational plans and forecasts in manufacturing, human resources, finance, sales and marketing. The disconnects between planning, operations and analysis are one of the main challenges of analytic systems, but they also represent one of the biggest opportunities.

While analytics has emerged as a top priority because of its ability to provide deeper insight into business performance, there are obstacles that prevent its full potential from being realized. The proliferation of analytic tools across the organization and the corresponding data silos that exist make it difficult for you to leverage best practices, collaborate across functions and confidently see one version of the truth. People need to have a single, simple way of defining KPI’s so they can quickly align around complete, accurate and timely information and spend their time solving problems instead of gathering and correlating data.

In today’s volatile economic and market environment, analytic requirements change frequently, often exceeding 50% per year. To operate as a competitive organization you must have the capability to adapt to changing business requirements. Static, inflexible systems are a drag on agile business management. You need the ability to quickly visualize the status of performance that’s relevant to your role regardless of location – at your desk, in the factory or on the road – and have the confidence of knowing that you’re seeing current, accurate information.

Evolving from Efficiency to Effectiveness to Transformation

Given these daunting challenges, how do you get started and what's the best strategy for building an analytic roadmap for your company? Oracle believes that there are three major stages in deploying analytics.  First, focus on improving operational efficiency by making insights pervasive and consistent across the organization while lowering total cost of ownership.    Second, analytic initiatives should aim to increase the operational effectiveness of decision makers.  Beyond gaining insight, operational effectiveness is about cascading strategy into operations, and creating more dynamic financial and operational plans that react and respond to a changing environment.

Third and most important, when deployed strategically analytics can be transformative for your company. When linking insights to action, decisions can be optimized and advantage can be created.  By combining unstructured data with data warehouse, new insights and patterns can found.  And through engineered systems new analytic applications can be created with extreme performance advantages.

Efficiency – Doing the Current Things Right

BI Platform Standardization. To create greater operational efficiency you need to standardize on an enterprise platform that can meet the diverse and continuously changing needs of your organization. The Oracle BI Foundation integrates the capabilities of multiple BI tools into a single, unified technology platform that supports the full spectrum of analytic requirements, including reports, dashboards, scorecards, scenario analysis, and ad-hoc query and analysis.

A unique Common Enterprise Information Model centralizes all metrics, calculations and assumptions which provide your users with confidence in the data, because the definitions are consistent regardless of where or how the information is accessed. Your users are insulated from the complexities of traditional BI tools enabling “self-service BI” which minimizes their reliance on IT to generate reports.

Workforces are increasingly mobile and the demand for access ‘on the go’ is exploding due the popularity of the Apple iPad and other tablet devices. In a recent report, Gartner estimates that over the next several years more than 33% of BI information will be consumed on mobile devices. Oracle identified this trend long ago and includes mobile capability in the Oracle BI Foundation. Unlike pure-play mobile BI vendors, Oracle’s solution shares common metadata, common definitions, and common infrastructure across web and mobile devices, meaning that you can see exactly the same information regardless of where you want to go.

Effectiveness – Doing the Right Things

Enterprise Performance Management. Core to improving operational effectiveness is linking strategy with execution. Leading companies have turned to Enterprise Performance Management (EPM) solutions to achieve this objective. Oracle leads this market with the most complete suite of EPM applications that span strategic, financial and operational planning areas.

Customers in all industries use EPM applications to drive agility and alignment into their enterprise planning processes. Annual financial plans are informed by strategic assumptions. These include product, customer, and business unit profitability models that can be created using Oracle’s cost management and profitability application. Through direct integration with ERP systems, baseline plans, forecasts and monthly updates can be informed by up to the minute actual information from the general ledger. Top down and bottoms up approaches can be reconciled and rolling forecasts provide more meaning to variance analysis. Additionally, Oracle has extended our enterprise planning solution to address the specific needs of workforce planning, capital asset planning and project planning. These modular solutions directly integrate with Oracle’s financial planning application to ensure that plans are connected and aligned to support the ongoing operational needs of your company.

Packaged Analytic Applications. Another key attribute of improving operational effectiveness is to challenge conventional wisdom and not build data warehouses from scratch. Although every company has unique reporting and analysis requirements, many can be addressed through packaged analytic applications.

The basic analytic requirements of your finance, HR, sales and procurement teams typically do not vary widely among different companies or industries. For example, finance departments in nearly all private and public sectors need to continuously monitor trends and variances of general ledger accounts, receivables, fixed assets and payable. Oracle is the only vendor that offers a comprehensive family of more than 80 packaged analytic applications for every major business function.

By using Oracle BI Applications, finance professionals have visibility into operating expenses, account balances and purchasing patterns. HR professionals can gain insights into global headcount status, attrition rates and the effectiveness of learning programs. Procurement and Operations professionals can track supplier performance and inventory trends, trade discounts and warranty return costs. In marketing, your managers can monitor the efficacy of promotions and campaigns and make adjustments to maximize success rates. Your sales managers can more effectively forecast revenues and transactions, manage pipeline and track key opportunities. Service teams can optimize call center and depot staffing levels, identify problem areas that need attention, and respond more effectively to customer service call volumes.

All of Oracle’s BI Applications are built on the Oracle BI Foundation, and are pre-integrated with Oracle ERP and CRM applications. Each application features dashboards, metrics, KPI’s and derived calculations based on industry best practices from over 3,000 deployments. Each application can be deployed individually or together, as each module conforms to a common enterprise data model.

Transformation – Doing New Things

Intelligent Business Process. To reach a transformative level you will need to consider a way of linking your planning and analytic systems with the operational systems that run the business on a daily basis. Oracle’s analytic strategy enables you to create an Intelligent Business Process that is connected and continuous.  It supports all three aspects of performance management including shaping strategy through financial and operational planning, taking action to execute the strategy across the business operations and measuring the results to enable fact-based decisions and continuous improvement. 

Delivering on the promise of the Intelligent Business Process requires that analytics be tightly integrated with operational processes. IDC coined the term “Closed Loop Analytics”, describing this type of integration but until recently, the promise has not been fulfilled. Conventional BI platforms can deliver insight in the form of dashboards and reports, but in order to take action based on that insight, you typically need to leave the BI environment and enter some other system. Oracle has introduced an innovative new capability the Oracle BI Foundation that breaks down the traditional walls between analysis and execution by allowing you to initiate actions, such as workflows and notifications, directly from your reports and dashboards. This direct connection of insight with action has also been built into Oracle’s Fusion Applications as a core capability. The compelling result is that your business process is now continuous – you can discover variances, drill to root cause, assess alternatives and initiate action all within the same system – and confidently move forward with the right action at the right time.

Visualization. Linking cause and effect, identifying patterns buried in massive databases has been the purview of statisticians and business analysts. Visualization tools have provided partial solutions but are constrained by data capacity or memory. To overcome these challenges, Oracle developed the industry’s first engineered system which combines analytic software, an in-memory database and hardware platform all built, tested and optimized together. Unlike stand-alone data discovery tools, Oracle Exalytics provided extreme performance and unconstrained visualization allowing users to navigate and explore information at the speed of thought.

Big Data. It’s estimated that 95% of the worlds’ data is unstructured, which is driving the need to store, combine, access and analyze this “big data”. Whether it’s social media activity, web logs, warranty claims, call center activity, movement of assets with RFID tags or sensor data, the need to gain insight on these new sources is growing. Oracle offers the broadest portfolio of solutions to help you acquire, organize analyze this diverse data alongside your existing enterprise to find new insights and capitalize on hidden relationships. The Oracle Big Data Appliance is the first engineered system optimized for acquiring, organizing and loading unstructured data into Oracle Database 11g. Oracle R Enterprise allows you to run existing R applications directly against data stored in Oracle Database 11g.

How Oracle Can Help

To address the complex challenges associated with driving improvement in business performance, Oracle’s analytic strategy enables you to progress from operational efficiency to operational effectiveness to business transformation. This strategy incorporates a powerful and flexible BI Foundation which supports an extensive range of analytic needs, packaged analytic applications based on business best practices, and EPM solutions that link strategy with execution. It lets you access data from all types of sources, consume information when and where you choose, and expand or customize your analytic environment based on business requirements rather than on technology restrictions.

What does it mean? By establishing a reliable and open foundation, you can get information when you want it, visualize results and trends in the right context, and have the confidence of knowing that there is one source of truth. By creating an Intelligent Business Process, you will connect strategy with operations and analysis, and move towards fact-based decisions. This approach is the basis for continuous improvement and for increasing the competitiveness of your organization in a rapidly changing world.

Monday Feb 13, 2012

Expanding Our Business Intelligence Horizons

It is a real pleasure to start blogging here along side my new colleagues from Oracle after going thru the on-boarding process to become a new Oracle employee post the acquisition of Endeca by Oracle announced this past fall. Speaking for our entire team,  we are very excited to be part of the Oracle Business Intelligence product line and team. Its been an amazing adventure. We really appreciate all the support from our customers who have been huge advocate of what has been known as Endeca Latitude and now known as Oracle Endeca Information Discovery.

My goals with my blog posts are to share with you observations, perspectives and insight on the Data Discovery market and technology as well as our product and its capabilities. My style is to have a dialogue, tell a story, dig down into technical topics, use cases and bring you additional insight on the importance of Data Discovery. I hope you will enjoy reading these blog posts as well as others who are contributing to this blog.

If this is your first exposure to Oracle Endeca Information Discovery, you will find the various features and benefits of our product at this landing page on  oracle.com You will also find a data sheet that will walk you thru some of the core elements of our platform. This is a good starting point for getting oriented to our product line.

For my next post, I'll discuss some of the core use cases for Oracle Endeca Information Discovery. In the meantime, thanks again for visiting the blog.

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