Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Business Intelligence”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

The NASA Program Management Tool: A New Vision in Business Intelligence

This paper describes a novel approach to business intelligence and program management for large technology enterprises like the U.S. National Aeronautics and Space Administration (NASA). Two key distinctions of the approach are that 1) standard business documents are the user interface, and 2) a "schema-less" XML database enables flexible integration of technology information for use by both humans and machines in a highly dynamic environment. The implementation utilizes patent-pending NASA software called the NASA Program Management Tool (PMT) and its underlying "schema-less" XML database called Netmark. Initial benefits of PMT include elimination of discrepancies between business documents that use the same information and "paperwork reduction" for program and project management in the form of reducing the effort required to understand standard reporting requirements and to comply with those reporting requirements. We project that the underlying approach to business intelligence will enable significant benefits in the timeliness, integrity and depth of business information available to decision makers on all organizational levels.

Maluf, David A.↗

Context-Enabled Business Intelligence

To truly understand context and apply it in business intelligence, it is vital to understand what context is and how it can be applied in addressing organizational needs. Context describes the facets of the environment that impact the way that end users interact with the system. Context includes aspects of location, chronology, access method, demographics, social influence/ relationships, end-user attitude/ emotional state, behavior/ past behavior, and presence. To be successful in making Business Intelligence content enabled, it is important to be able to capture the context of use user. With advances in technology, there are a number of ways in which this user based information can be gathered and exposed to enhance the overall end user experience.

97 MATHEMATICS AND COMPUTING↗

A Machine Learning Approach for Business Intelligence Analysis using Commercial Shipping Transaction Data

Business intelligence problems are particularly challenging due to the use of large volume and high velocity data in attempts to model and explain complex underlying phenomena. Incremental machine learning based approaches for summarizing trends and identifying anomalous behavior are often desirable in such conditions to assist domain experts in characterizing their data. The overall goal of this research is to develop a machine learning algorithm that enables predictive analysis on streaming data, detects changes and anomalies in the data, and can evolve based on the dynamic behavior of the data. Commercial shipping transaction data for the U.S. is used to develop and test a Naïve Bayes model that classifies several companies into lines of businesses and demonstrates an ability to predict when the behavior of these companies changes by venturing into other lines of businesses.

Bramer, Lisa M.↗

2020 Workplace and the Evolution of Business Intelligence

The work place is rapidly changing and will continue to change as the decade proceeds to 2020. Business Intelligence (BI) has many of the tools that will ensure that employees in this future work place can be successful and deal with these environmental changes. Ideas such as “swarming”, “hyper-connectedness”, “de-routinization of work” and “the collective” will morph employee engagement and those organizations with mature Business Intelligence practices will be prepared to support the success of their employees.

99 GENERAL AND MISCELLANEOUS↗

Business Intelligence Modeling in Launch Operations

This technology project is to advance an integrated Planning and Management Simulation Model for evaluation of risks, costs, and reliability of launch systems from Earth to Orbit for Space Exploration. The approach builds on research done in the NASA ARC/KSC developed Virtual Test Bed (VTB) to integrate architectural, operations process, and mission simulations for the purpose of evaluating enterprise level strategies to reduce cost, improve systems operability, and reduce mission risks. The objectives are to understand the interdependency of architecture and process on recurring launch cost of operations, provide management a tool for assessing systems safety and dependability versus cost, and leverage lessons learned and empirical models from Shuttle and International Space Station to validate models applied to Exploration. The systems-of-systems concept is built to balance the conflicting objectives of safety, reliability, and process strategy in order to achieve long term sustainability. A planning and analysis test bed is needed for evaluation of enterprise level options and strategies for transit and launch systems as well as surface and orbital systems. This environment can also support agency simulation .based acquisition process objectives. The technology development approach is based on the collaborative effort set forth in the VTB's integrating operations. process models, systems and environment models, and cost models as a comprehensive disciplined enterprise analysis environment. Significant emphasis is being placed on adapting root cause from existing Shuttle operations to exploration. Technical challenges include cost model validation, integration of parametric models with discrete event process and systems simulations. and large-scale simulation integration. The enterprise architecture is required for coherent integration of systems models. It will also require a plan for evolution over the life of the program. The proposed technology will produce long-term benefits in support of the NASA objectives for simulation based acquisition, will improve the ability to assess architectural options verses safety/risk for future exploration systems, and will facilitate incorporation of operability as a systems design consideration, reducing overall life cycle cost for future systems. The future of business intelligence of space exploration will focus on the intelligent system-of-systems real-time enterprise. In present business intelligence, a number of technologies that are most relevant to space exploration are experiencing the greatest change. Emerging patterns of set of processes rather than organizational units leading to end-to-end automation is becoming a major objective of enterprise information technology. The cost element is a leading factor of future exploration systems.

Bardina, Jorge E.↗

Business intelligence for human resources. Toward a new paradigm for report development and delivery

As a corporate workforce grows, managers need more information close at hand to make decisions for the company. As every scientist knows, we can’t judge, let alone improve, something that can’t be measured. Thus, firms that are committed to constant improvement generate reports on various business metrics in order to make informed decisions. Sandia National Labs is no exception. Enterprise business intelligence (BI) is very important to keep such a large organization on the right track, as it signals any adjustments that may be required to stay the course. Like teams in other fields, Sandia’s HR Reporting wants to provide the most valuable Workforce BI possible, and it is considering a change in reporting paradigm to achieve that.

99 GENERAL AND MISCELLANEOUS↗

Use of Business Intelligence Tools in the DSN

JPL has operated the Deep Space Network (DSN) on behalf of NASA since the 1960's. Over the last two decades, the DSN budget has generally declined in real-year dollars while the aging assets required more attention, and the missions became more complex. As a result, the DSN budget has been increasingly consumed by Operations and Maintenance (O&M), significantly reducing the funding wedge available for technology investment and for enhancing the DSN capability and capacity. Responding to this budget squeeze, the DSN launched an effort to improve the cost-efficiency of the O&M. In this paper we: elaborate on the methodology adopted to understand "where the time and money are used"-surprisingly, most of the data required for metrics development was readily available in existing databases-we have used commercial Business Intelligence (BI) tools to mine the databases and automatically extract the metrics (including trends) and distribute them weekly to interested parties; describe the DSN-specific effort to convert the intuitive understanding of "where the time is spent" into meaningful and actionable metrics that quantify use of resources, highlight candidate areas of improvement, and establish trends; and discuss the use of the BI-derived metrics-one of the most fascinating processes was the dramatic improvement in some areas of operations when the metrics were shared with the operators-the visibility of the metrics, and a self-induced competition, caused almost immediate improvement in some areas. While the near-term use of the metrics is to quantify the processes and track the improvement, these techniques will be just as useful in monitoring the process, e.g. as an input to a lean-six-sigma process.

Metrics↗

The Cure for Ailing Self-Service Business Intelligence

There are many reasons that self-service models fail. Furthermore, these reasons are directly applicable in the management of self-service business inteligence modeling. Our article expands upon the reasons for failure and suggests how self-service models can be made successful through implementation of a centralized approach to development, testing, implementation and support for the delivery of decision making information.

99 GENERAL AND MISCELLANEOUS↗

Developing a Business Intelligence Process for a Training Module in SharePoint 2010

Prior to this project, training information for the employees of the National Center for Critical Processing and Storage (NCCIPS) was stored in an array of unrelated spreadsheets and SharePoint lists that had to be manually updated. By developing a content management system through a web application platform named SharePoint, this training system is now highly automated and provides a much less intensive method of storing training data and scheduling training courses. This system was developed by using SharePoint Designer and laying out the data structure for the interaction between different lists of data about the employees. The automation of data population inside of the lists was accomplished by implementing SharePoint workflows which essentially lay out the logic for how data is connected and calculated between certain lists. The resulting training system is constructed from a combination of five lists of data with a single list acting as the user-friendly interface. This interface is populated with the courses required for each employee and includes past and future information about course requirements. The employees of NCCIPS now have the ability to view, log, and schedule their training information and courses with much more ease. This system will relieve a significant amount of manual input and serve as a powerful informational resource for the employees of NCCIPS in the future.

Schmidtchen, Bryce↗

Watson and Siri: The Rise of the BI Smart Machine

Over the past few years, the industry has seen significant evolution in the area of human computer interaction. The era of the smart machines is upon us, with automation taking on a more advanced role than ever before, permeating into areas that have traditionally only been fulfilled by human beings. This movement has the potential of fundamentally altering the way that business intelligence is executed across the industry and the role that business intelligence has in all aspects of decision making.

99 GENERAL AND MISCELLANEOUS↗

Service Quality Assessment for NASA's Deep Space Network: No Longer a Luxury

When NASA's Deep Space Network (DSN) was established almost a half century ago, the concept of computer-based service delivery was impractical or infeasible due to the state of information technology As a result, the interface the DSN exposes to its customers tends to be equipment-centric, lacking a clear demarcation between the DSN and the mission operation systems (MOS) of its customers. As the number of customers has continued to increase, the need to improve efficiency and minimize costs has grown. This growth has been the impetus for a DSN transformation from an equipment-forrent provider to a provider of standard services. Service orientation naturally leads to requirements for service management, including proactive measurement of service quality and service levels as well as the efficiency of internal processes and the performance of service provisioning systems. DSN System Engineering has surveyed industry offerings to determine if commercial successes in decision support and Business Intelligence (BI) solutions can be applied to the DSN. A pilot project was initiated, and subsequently executed to determine the feasibility of repurposing a commercial Business Intelligence platform for engineering analysis in conjunction with the platform's intended business reporting and analysis functions.

Operations Efficiency↗

Consolidation and Centralization of Waste Operations Business Systems - 12319

This abstract provides a comprehensive plan supporting the continued development and integration of all waste operations and waste management business systems. These include existing systems such as ATMS (Automated Transportation Management System), RadCalc, RFITS (Radio Frequency Identification Transportation System) Programs as well as incorporating key components of existing government developed waste management systems and COTS (Computer Off The Shelf) applications in order to deliver a truly integrated waste tracking and management business system. Some of these existing systems to be integrated include IWTS at Idaho National Lab, WIMS at Sandia National Lab and others. The aggregation of data and consolidation into a single comprehensive business system delivers best practices in lifecycle waste management processes to be delivered across the Department of Energy facilities. This concept exists to reduce operational costs to the federal government by combining key business systems into a centralized enterprise application following the methodology that as contractors change, the tools they use to manage DOE's assets do not. IWITS is one efficient representation of a sound architecture currently supporting multiple DOE sites from a waste management solution. The integration of ATMS, RadCalc and RFITS and the concept like IWITS into a single solution for DOE contractors will result in significant savings and increased efficiencies for DOE. Building continuity and solving collective problems can only be achieved through mass collaboration, resulting in an online community that DOE contractors and subcontractors access common applications, allowing for the collection of business intelligence at an unprecedented level. This is a fundamental shift from a solely 'for profit' business model to a 'for purpose' business model. To the conventional-minded, putting values before profit is an unfamiliar and unnatural way for a contractor to operate - unless however; your objective is to build a strong, strategic alliance across the enterprise in order to execute an unprecedented change in waste management, transportation and logistical operations. The success of such an initiative can be achieved by creating a responsible framework by enabling key individuals to 'own' the sustainability of the program. This includes the strategic collaboration of responsible revolutionaries covering application developers, information owners and federal stakeholders to ensure compliance, security and risk management are 'baked' into the process and sustainability is fostered through continued innovation by both technology and application functionality. This ensures that working software can adapt to changing circumstances and is the principle measure of the success of the program. The consolidation of waste management business systems must be achieved in order to realize efficiencies in information technology portfolio management, data integrity, business intelligence and the lifecycle management of hazardous materials within the DOE enterprise architecture. By identifying best practices across the enterprise and aggregating computational and application development resources, you can provide a unified, holistic solution serviceable from a single location while being accessed from anywhere. The business impact of integrating and delivering a unified solution would reduce costs to the Department of Energy within the first year of deployment with increased savings annually. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Requirements for Predictive Analytics

It is important to have a clear understanding of how traditional Business Intelligence (BI) and analytics are different and how they fit together in optimizing organizational decision making. With tradition BI, activities are focused primarily on providing context to enhance a known set of information through aggregation, data cleansing and delivery mechanisms. As these organizations mature their BI ecosystems, they achieve a clearer picture of the key performance indicators signaling the relative health of their operations. Organizations that embark on activities surrounding predictive analytics and data mining go beyond simply presenting the data in a manner that will allow decisions makers to have a complete context around the information. These organizations generate models based on known information and then apply other organizational data against these models to reveal unknown information.

97 MATHEMATICS AND COMPUTING↗

Achieving Fast Operational Intelligence in NASA's Deep Space Network Through Complex Event Processing

NASA’s Deep Space Network (DSN) is a complex, global project, in which the expertise of human operators remain crucial for its successful operation. To find ways to save costs in operations and to improve its services, a number of modernization efforts are underway in the DSN. One such effort is a research and technology development task at the Jet Propulsion Laboratory that is investigating the use of complex event processing (CEP) for intelligent assessment of situations, trend analysis, and advanced automation. The technology leverages the significant business intelligence (BI) and data science advancements made in the enterprise industries over the last several years. The open source big data processing engine Apache SparkTM and the high-throughput, distributed messaging system Apache Kafka form the core of the DSN Complex Event Processing (DCEP) framework. This paper discusses the system engineering perspective of why achieving efficient, lower-cost operations in the DSN is a challenging problem, how the DCEP system handles the use cases that help realize intelligent operations, and how this solution fits into the overall model of the planned DSN Follow-the- Sun Operations (FtSO).

Choi, Joshua S.↗