Disclosed are database systems, methods, systems, and computer program products for providing tabular data in a social network feed. In some implementations, a server of a database system stores, in a database, social network feed data comprising a plurality of feed items as data objects. The server also stores, in a database, tabular data as data objects. The server shares the social network feed data and the tabular data in a social network feed displayable to present the feed items and the tabular data in a user interface, the tabular data being presentable in the user interface in a tabular format. The user interface may receive shareable user commentary regarding the tabular data. The stored tabular data may be editable by users of the database system. The social network feed may be updated to comprise notifications of edits to the tabular data.

Disclosed here is a visual collaboration software including multiple digital canvas and multiple tools enabling collaboration among multiple users by enabling creation and sharing of visual information including text and drawings. The visual collaboration software obtains from a second software, e.g., a project management software, a file or a portion of the file, and displays the file or the portion in one of the multiple digital canvases. In one embodiment, the visual collaboration software can enable the user to interact with the file obtained from the second software and can pass the modifications to the file to the second software. In another embodiment, the visual collaboration software can only display the file or the portion of the file in one of the multiple digital canvases, and an interaction between the user and the file has to be passed to the second software to compute to the effect of the interaction.

Disclosed here is a visual collaboration software including multiple digital canvas and multiple tools enabling collaboration among multiple users by enabling creation and sharing of visual information including text and drawings. The visual collaboration software obtains from a second software, e.g., a project management software, a file or a portion of the file, and displays the file or the portion in one of the multiple digital canvases. In one embodiment, the visual collaboration software can enable the user to interact with the file obtained from the second software and can pass the modifications to the file to the second software. In another embodiment, the visual collaboration software can only display the file or the portion of the file in one of the multiple digital canvases, and an interaction between the user and the file has to be passed to the second software to compute to the effect of the interaction.

Systems and methods extract flat data units from a non-flat input, such as a spreadsheet comprising tables organized according to a hierarchy. First, the non-flat input is read (e.g., using pandas in combination with openpyxl) to create a flat dataframe comprising the content of the non-flat input. Next, individual flat data units (e.g., spreadsheet tables) are recognized and split from the dataframe based upon the appearance of blank rows and/or columns. Headers present in the flat data units are determined (e.g., based upon alphabetic cell text, bolded cell text, and/or early position of the cell in a column), and then connections between the flat data units are identified. Based upon the connections, individual flat data units are merged together. The resulting merged flat data units are subsequently available for consumption, for example user reports of content, and/or conversion to a new non-flat format (e.g., relational database schema).

Systems and methods extract flat data units from a non-flat input, such as a spreadsheet comprising tables organized according to a hierarchy. First, the non-flat input is read (e.g., using pandas in combination with openpyxl) to create a flat dataframe comprising the content of the non-flat input. Next, individual flat data units (e.g., spreadsheet tables) are recognized and split from the dataframe based upon the appearance of blank rows and/or columns. Headers present in the flat data units are determined (e.g., based upon alphabetic cell text, bolded cell text, and/or early position of the cell in a column), and then connections between the flat data units are identified. Based upon the connections, individual flat data units are merged together. The resulting merged flat data units are subsequently available for consumption, for example user reports of content, and/or conversion to a new non-flat format (e.g., relational database schema).

Disclosed are systems and computer implemented methods for providing quantum computing as a service. According to one embodiment the system includes a frontend computing system storing a frontend computer program, a backend computing system, and a quantum computer, the frontend computer program being a spreadsheet application configured to receive a service request from a user, the service request comprising service request parameters and input data. The frontend computing system sends the service request to the backend computing system, which is configured to encode it to a service job in a format suitable for the quantum computer to execute, and to submit the service job to the quantum computer. The quantum computer is configured to execute the service job and to provide service job results to the backend computing system, which translates them into results data and sends them to the frontend computing system.

Disclosed are systems and computer implemented methods for providing quantum computing as a service. According to one embodiment the system includes a frontend computing system storing a frontend computer program, a backend computing system, and a quantum computer, the frontend computer program being a spreadsheet application configured to receive a service request from a user, the service request comprising service request parameters and input data. The frontend computing system sends the service request to the backend computing system, which is configured to encode it to a service job in a format suitable for the quantum computer to execute, and to submit the service job to the quantum computer. The quantum computer is configured to execute the service job and to provide service job results to the backend computing system, which translates them into results data and sends them to the frontend computing system.

A system and method for end-to-end transaction management, for example, for a structured finance market. The system and method digitizes and deconstructs complex interconnected transaction documents. The system creates transparency around the complexities of the transactions, generating significant efficiencies for existing market participants and enabling access to previously hidden and/or inaccessible data. In some embodiments, the platform supports a selected ecosystem (compared to specific use-cases within a market vertical) with a seamless integration of frameworks and schemas for the organization and structure of provisions, analytical tools extracting the required data, and the creation of metrics to informatively assess and calibrate the market. The system advantageously creates a digital language providing a tool, which will further enable the digitization of the finance ecosystem.

A processor-implemented method includes (i) obtaining raw data and value of a parameter in a column of tabular data, (ii) defining, based on user input, a smart column with tabular data prediction generated from raw data, (iii) validating, based on user input, a first label and a second label corresponding respectively to a first and a second predefined category to obtain a first and a second user-validated label respectively, (iv) detecting error in training set of the predictive AI model when there is a mismatch between a value from predictive AI model and user-validated label, (v) automatically generating a formula for the tabular data prediction to fix the error in training set, (vi) validating the first formula data prediction based on user input to obtain a user-validated formula, and (vii) automatically generating a first tabular data prediction in the smart column using user-validated formula to some of the raw data.

Systems and methods are directed to providing efficient and fast invocation of concurrent sheet defined functions (SDFs) including dynamic arrays by front-loading the work. At SDF creation time, a SDF cell table, a formula table, and a spill area table are generated. The SDF cell table represents cells from a worksheet that are used for the SDF. The formula table comprises an index of formulas used by the SDF, whereby index identifiers are stored in cells of the SDF cell table. The spill area table comprises an index of spill areas where each dynamic array may automatically spill into. The SDF cell table, formula table, and spill area table are shared between a plurality of invocations of the SDF during invocation time.