Abstract: A method and system for persisting data are provided. Batch data is periodically extracted via a computer system from at least one primary data source. Batch data is transformed via the computer system. The batch data is loaded, via the computer system, into a database. Real-time data is continuously received from at least one secondary data source. The received real-time data is indexed in an index. Business intelligence reports are generated from both the real-time data in the index and the batch data in the database.

Abstract: Systems and methods for computer memory management by a memory coordinator and a plurality of memory consumers. An urgency and memory quota of each memory consumer is initialized by the memory coordinator, which then adjusts the memory quota of each memory consumer such that the sum of the memory quota of each memory consumer does not exceed a finite amount of computer memory. Each memory consumer adjusts its memory usage in response to the quota input and urgency input from the memory coordinator.

Abstract: A method and system for a machine learning cluster analysis of historical lead time data, which is augmented by one or more features. The data can also be divided into groups, based on time-density of the data, with clustering performed on each group. Furthermore, clustering can also be projected onto two dimensions. In addition, the historical lead time data is separated into a plurality of tolerance zones based on tolerance criteria. The clusters are separated in accordance with a tolerance zone of each group; and further separated according to one or more lead time identifiers to provide one or more separated clusters.

Abstract: The systems and methods described here can reduce the storage space required (memory and/or disk) to store certain types of data, provide efficient (fast) creation, modification and retrieval of such data, and support such data within the framework of a multi-version database. In some embodiments, the systems and methods can store each field of a set of records as a vector of values, e.g., a data vector. A set of records can be represented using a vector hash vector, or “vhash” vector, wherein each element of the vhash vector contains a unique identifier of a data vector, based on a cryptographic hash of the data vector. A header table can store associations between labels and “vhash” vectors that pertain to those labels. Identical data vectors can be re-used between different record sets or vhash vectors needing that vector, thus saving space.

Abstract: The systems and methods described here can reduce the storage space required (memory and/or disk) to store certain types of data, provide efficient (fast) creation, modification and retrieval of such data, and support such data within the framework of a multi-version database. In some embodiments, the systems and methods can store each field of a set of records as a vector of values, e.g., a data vector. A set of records can be represented using a vector id vector, or “vid” vector, wherein each element of the vid vector contains a reference to the memory location of a data vector. A header table can store associations between labels and “vid” vectors that pertain to those labels. Identical data vectors can be re-used between different record sets or vid vectors needing that vector, thus saving space.

Abstract: A method to determine if a value is present in a storage hierarchy which comprises initialization of a range of the collection that resides on a first storage device that is in a tier slower than a fastest tier of a storage hierarchy; partitioning the range into disjointed range partitions such that a first subset of the range partitions is designated as cached and a second subset is designated as uncached; partitioning the collection into a subset of uncached data and cached data; copying, the subset of the collection which lies in the one or more cached range partitions into a cache, wherein the cache resides on a second storage device that is in a tier faster than the first storage device; determination of a target range partition to which the value belongs, and determining if the target range partition is cached or uncached.

Abstract: A system and method for flexible pipeline generation. The method includes: generating two or more tasks, the two or more tasks define at least a portion of the pipeline; generating a reconfigurable workflow for defining associations for the two or more tasks, the workflow includes: mapping the output of at least one of the tasks with a culminating output; mapping the input of at least one of the tasks with the output of at least one of the other tasks; and mapping the input of at least one of the tasks with an originating input; and executing the pipeline using the workflow for order of execution of the two or more tasks.

Abstract: A dynamic supply chain planning system for analysis of historical lead time data that uses machine learning algorithms to forecast future lead times based on historical lead time data, weather data and financial data related to locations and dates within the supply chain.

Abstract: A dynamic supply chain planning system for analysis of historical lead time data that uses machine learning algorithms to forecast future lead times based on historical lead time data, and to divide historical lead time data into clusters based on seasonality and linearity. The machine learning results are further processed to adjust future planned lead times and to identify sources in the supply chain that contribute to large deviations between historical planned lead times and actual lead times.

Abstract: A system for memory management that comprises: a computing system having a finite amount of memory and a physical computer readable storage memory readable by a processing circuit and storing instructions for execution by the circuit to: set, by a memory coordinator, the urgency of each memory consumer; adjust, by the memory coordinator, the memory quota of each memory consumer—such that the sum of the memory quota of each memory consumer does not exceed the memory; and adjust, by each memory consumer, its memory usage in response to a quota input and an urgency input from the memory coordinator to the memory consumer. The memory is managed by a memory coordinator and memory consumers; and consumed by the memory consumers. Each memory consumer has: a memory quota, an urgency and a memory usage. Also, the urgency of each memory consumer increases as the sum of the memory usage of the plurality of memory consumers approaches the finite amount of memory.

Abstract: A business analytics conversational tool comprising: a device comprising a communication channel, a natural language processor (NLP), a fulfillment application program interface (F-API), a database application program interface (D-API), and a business management database; wherein: the NLP receives a user-input from a user through the communication channel; the NLP deduces an intent of the user-input; the NLP communicates the intent to the F-API; the F-API communicates a request for data associated with the intent to the database via the D-API; the D-API communicates the data associated with the intent to the F-API; the F-API converts the data associated with the intent to conversational form and sends the conversational form for voice output through the communication channel.

Abstract: Large and complex data sets can be difficult to view on devices with small screens, such as on smartphones, or in small windows on devices with large screens. The presently disclosed systems, methods and apparatus can determine characteristics associated with a display used to display a requested resource. Based on these determined characteristics, the systems and methods can determine whether the requested resource should be reformatted to fit the display. The requested resource can be reformatted to allow a user to consume complex data on a small display easily and effectively. In some embodiments, this can be done by ensuring that the current data context, previously provided by row/column headers, are always in view in a compact format.

Abstract: In accordance with the disclosed subject matter, systems and methods are provided for improving performance of a versioned database. Embodiments include systems and methods for improving performance of versioned databases by selectively loading portions of database files on disk into memory. Embodiments also include systems and methods for capturing and consolidating or condensing transaction logs into database files for loading.

Abstract: A system for calculating analytics uses a relational database to store inputs, calculates results, and stores them in cache. The system also includes an access layer that provides a unified view of the data in server. A dynamic access layer is generated at runtime to run an analytic to provide a flexible framework for creating business logic.

Abstract: In accordance with the disclosed subject matter, systems and methods are provided for improving performance of a versioned database. Embodiments include systems and methods for improving performance of versioned databases by selectively loading portions of database files on disk into memory. Embodiments also include systems and methods for capturing and consolidating or condensing transaction logs into database files for loading.

Abstract: Certain embodiments include methods, systems, and non-transitory computer program products for fulfilling supply and demand. The method includes receiving a demand for a resource, and determining a plurality of relationships among related resources. The related resources can represent dependent resources needing to be fulfilled in order to fulfill the demand for the resource. The relationships can group the related resources into levels according to the dependencies. For each level, the method further includes processing dependent resources depth-first proceeding down levels, if an importance of the related resources indicates there are no more important related resources to process at the level, and interrupting the depth-first processing to process related resources breadth-first at the level, if the importance of the related resources indicates there are more important related resources at the level.

Abstract: A system for calculating analytics uses a relational database to store inputs, calculates results, and stores them in cache. The system also includes an access layer that provides a unified view of the data in server. A dynamic access layer is generated at runtime to run an analytic to provide a flexible framework for creating business logic.

Abstract: A scheduler combines characteristics of a forward and backward schedulers to determine a schedule for activities that require the use of resources. The system handles conflicting requirements for resources by considering target dates and the relative priority of the activities. As a result, higher priority activities are more likely to be scheduled to complete on or before their target date than are lower priority activities.