Maintaining dataset integrity during ingestion of user interface data

1 . A computer-implemented method, comprising:

connecting an application associated with a user interface (UI) to a dataset and a software robot;

ingesting, by the software robot, data from one or more fields of the UI, wherein the ingesting includes:

monitoring user interactions of entering the data into the one or more fields of the UI; and

collecting the data entered into the one or more fields of the UI;

obtaining expected data for the one or more fields of the UI, wherein the obtaining of the expected data includes:

executing a web scrapping process for the one or more fields of the UI to obtain first data;

adding the first data to the expected data; and

obtaining second data from data backend document object model (DOM) values, wherein the expected data includes data in corresponding entries of the dataset, the first data, and the second data;

comparing, by the application, the ingested data with the expected data based on a data similarity technique;

identifying, by the application, one or more inconsistencies between the ingested data and the expected data based on the comparing, wherein

the one or more inconsistencies comprise a lack of correlation between the expected data and the ingested data, and

the identifying of the one or more inconsistencies is performed prior to entering the ingested data into the dataset; and

performing, by the application, one or more remedial actions on at least one of the ingested data or the dataset, based on the identifying of the one or more inconsistencies.

2 . The computer-implemented method of claim 1 , wherein the data from the one or more fields of the UI is automatically and continuously checked for accuracy during the ingesting of the data.

3 . The computer-implemented method of claim 1 , wherein the ingesting further includes automating a set of tasks, and collecting data from the set of tasks as the set of tasks is performed or completed.

4 . The computer-implemented method of claim 1 , further comprising:

performing optical character recognition of the UI; and

adding one or more features, recognized from the optical character recognition, to the expected data.

5 . The computer-implemented method of claim 1 , further comprising:

detecting on screen data; and

recognizing patterns or anomalies in the dataset using a machine learning (ML) model trained on keywords and primary keys of the dataset, wherein the recognizing is based on the detected on screen data.

6 . The computer-implemented method of claim 1 , further comprising determining, using a machine learning (ML) model, whether a relationship exists between the ingested data and the expected data for the identifying of the one or more inconsistencies.

7 . The computer-implemented method of claim 1 , wherein the one or more remedial actions include flagging the data in the dataset based on the identifying of the one or more inconsistencies.

8 . The computer-implemented method of claim 1 , wherein

the one or more remedial actions include replacing a corresponding value in the dataset with an ingested data value of the ingested data, and

the replacing is based on the identifying of the one or more inconsistencies between the corresponding value and the ingested data value.

9 . The computer-implemented method of claim 1 , wherein the one or more remedial actions include arbitrating a conflict between two or more ingested values of the ingested data.

10 . The computer-implemented method of claim 1 , wherein

the UI is associated with a web browser, and

the web browser is used for the ingesting of the data.

11 . A computer system comprising a memory having computer readable instructions, and one or more processors for executing the computer readable instructions to configure the computer system to perform operations, the operations comprising:

connecting an application associated with a user interface (UI) to a dataset and a software robot;

ingesting, by the software robot, data from one or more fields of the UI, wherein the ingesting includes:

monitoring user interactions of entering the data into the one or more fields of the UI; and

collecting the data entered into the one or more fields of the UI;

obtaining expected data for the one or more fields of the UI, wherein the obtaining of the expected data includes:

executing a web scrapping process for the one or more fields of the UI to obtain first data;

adding the first data to the expected data; and

obtaining second data from data backend document object model (DOM) values, wherein the expected data includes data in corresponding entries of the dataset, the first data, and the second data;

comparing, by the application, the ingested data with the expected data based on a data similarity technique;

identifying, by the application, one or more inconsistencies between the ingested data and the expected data based on the comparing, wherein

the one or more inconsistencies comprise a lack of correlation between the expected data and the ingested data, and

the identifying of the one or more inconsistencies is performed prior to entering the ingested data into the dataset; and

performing, by the application, one or more remedial actions on at least one of the ingested data or the dataset, based on the identifying of the one or more inconsistencies.

12 . The computer system of claim 11 , wherein

the computer system is a cloud-based system, and

the ingested data is received from the UI of an end user device.

13 . The computer system of claim 12 , wherein the operations further comprise:

performing optical character recognition of the UI; and

adding one or more features, recognized from the optical character recognition, to the expected data.

14 . The computer system of claim 12 , wherein the operations further comprise determining, using a machine learning (ML) model, whether a relationship exists between the ingested data and the expected data for the identifying of the one or more inconsistencies.

15 . A computer program product comprising one or more computer-readable memory devices encoded with data including instructions that, when executed, causes a processor set to execute operations for maintaining dataset integrity, the operations comprising:

connecting an application associated with a user interface (UI) to a dataset and a software robot;

ingesting, by the software robot, data from one or more fields of the UI, wherein the ingesting includes:

monitoring user interactions of entering the data into the one or more fields of the UI; and

collecting the data entered into the one or more fields of the UI;

obtaining expected data for the one or more fields of the UI, wherein the obtaining of the expected data includes:

executing a web scrapping process for the one or more fields of the UI to obtain first data;

adding the first data to the expected data; and

obtaining second data from data backend document object model (DOM) values, wherein the expected data includes data in corresponding entries of the dataset, the first data, and the second data;

comparing, by the application, the ingested data with the expected data based on a data similarity technique;

identifying, by the application, one or more inconsistencies between the ingested data and the expected data based on the comparing, wherein

the one or more inconsistencies comprise a lack of correlation between the expected data and the ingested data, and

the identifying of the one or more inconsistencies is performed prior to entering the ingested data into the dataset; and

performing, by the application, one or more remedial actions on at least one of the ingested data or the dataset, based on the identifying of the one or more inconsistencies.