Emc IP Holding Company LLC

Trax Technology Solutions Pte Ltd.

Ran Taig

Avitan Gefen

Omer Sagi

Amihai Savir

Yair Adato

Assaf Natanzon

Anat Parush Tzur

Oshry Ben-Harush

Alon Grubshtein

Mark Cook

A system for automatically identifying situations to withhold planogram incompliance notifications in a retail store is disclosed. The system has a processor that receives image data depicting products displayed on a store shelf from image sensors mounted in the retail store. The processor identifies a product type associated with the displayed products and determines a placement of products of that product type on the shelf. The processor accesses a planogram describing a desired placement of products and identifies, based on the planogram, a discrepancy between the determined placement of products and the desired placement of product. The processor determines whether a notice-override condition exists. If a notice-override condition exists, the processor, withholds issuance of a user-notification associated with the identified discrepancy. If a notice-override condition does not exist, the processor issues the user-notification associated with the identified discrepancy.

Withholding low confidence notification due to planogram incompliance

A system for reducing product shortage durations in retail stores based on analysis of image data is provided. The system may comprise: a communication interface configured to receive image data from retail stores indicative of a product shortage of a product type relative to information describing a placement of products of a product type on a store shelf; and at least one processor configured to: analyze the image data to detect occurrences of product shortages of the product type in the retail stores and determine durations associated with the occurrences; identify a common factor contributing to the duration of part of the occurrences of the product shortages; determine an action, associated with the at least one common factor, for potentially reducing product shortage durations of future shortages of the product type in the retail stores; and provide information associated with the identified action to an entity.

Aggregating product shortage information

Techniques are provided for data-driven scheduling of automated software program test suites. An exemplary method comprises: obtaining a plurality of test cases that test software programs; obtaining a failure likelihood for each of the plurality of test cases; and scheduling the test cases in an order based on the failure likelihoods. Generally, test cases that are more likely to fail are scheduled before test cases that are less likely to fail. Dependencies and/or priorities among the plurality of test cases are also optionally obtained and the scheduling of the test cases is based on the dependencies and/or priorities. The dependencies among the plurality of test cases comprise, for example, an indication of whether a given test case constrains one or more additional test cases.

Data-driven scheduling of automated software program test suites

A DNA storage system for binary digital data. The digital data is deduplicated is encoded into a format for representation in DNA, and DNA representing the data is synthesized and stored in pools in a primary library, a hash library and a data library. The primary library stores DNA for accessing a hash object in the hash library corresponding to a hash of the data, and the hash library stores DNA for accessing a data object in the data library that contains the data. The information in the libraries includes information identifying objects, including keys, unique identifiers (UIDs), pool identifiers, and primers.

DNA-based data center with deduplication capability

Embodiments include facilitating DNA storage of digital data including a plurality of data assets in a network by building a causal graph of the network and the relationship of the data assets; computing a value of each data asset; computing, using the causal graph and data values, a radius of recovery for each data asset; classifying each data asset as appropriate DNA stored by assigning a numerical ranking of each data asset; defining manual constraints and a DNA storage configuration; and generating a ranked list of recommended data assets for storing in the DNA storage using the classification, manual constraints and DNA storage configuration.

Automatic identification, definition and management of data for DNA storage systems

Flexible scheduling for backup jobs includes backup policies that allow for flexibility in scheduling execution time, and an automated data driven backup job execution scheduler. The scheduler balances load on the customer's and data protection system's resources using a dynamic pricing calculator that takes into account the real-time and predicted near-future status of the protection environment. The backup job scheduler includes a user interface that enables users to specify user-customized backup policies that enable flexibility in scheduling execution times and transparency in pricing.

Flexible scheduler for backups

Business Data Lake searching techniques are provided. A method comprises obtaining a graph representing tables of the Business Data Lake, where each node represents one table and edges between nodes represent foreign key connections; applying a node rank algorithm to determine a relevancy score of the tables based on a number of links to/from other tables; and, in response to a query: ranking a relevancy of query items based on a term frequency-based score to generate candidate results; extracting a candidate sub-graph based on the following: a top-L tables based on the term frequency-based score, and/or a top-M tables based on a topic model distance score for the given query and candidate items; enriching the extracted candidate sub-graph by adding new tables using an item-to-item collaborative filter where a similarity between two tables is measured based on a number of interactions; and ordering the tables in the enriched sub-graph based on the relevancy score and/or a user-to-item collaborative filter that evaluates past user interactions with prior results.

Business data lake search engine

Embodiments for finding a root cause of an anomaly in a network environment by representing assets in the network environment as respective nodes in a causal graph, wherein the nodes have a measurable quality that can be tracked and arcs between pairs of nodes represent causal relationships between nodes of the node pairs designating source nodes as processes at the top of a hierarchy of tracked processes, and sink nodes as processes at the bottom of the hierarchy and having characteristics of interest in the environment; detecting anomalies in the tracked processes embodied in the sink nodes; traversing the causal graph in a reverse order from a node in which an outlier is detected; and analyzing nodes along the traversal path to identify a node of the highest hierarchy that shows unusual behavior as the root cause.

Root cause analysis for protection storage devices using causal graphs

An automated agent for the causal mapping of complex environments. Specifically, a disclosed method and system entails the application of statistical tools, or causality tests, to measure the strength and direction of causal relations between two or more environment components. Further, the execution of the causality tests may be an offline process that may be triggered periodically to account for changes or updates to an environment over time.

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Beer Sheva, Israel

Ran Taig