Knowledge Hut

JULY 26, 2023

Data veracity refers to the reliability and accuracy of data, encompassing factors such as data quality, integrity, consistency, and completeness. It involves assessing the quality of the data itself through processes like data cleansing and validation, as well as evaluating the credibility and trustworthiness of data sources.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

Striim

FEBRUARY 5, 2024

Enhanced Data Quality Striim incorporates robust data quality measures such as validation rules and data cleansing processes. By enforcing data quality standards throughout the integration pipeline, Striim ensures the integrity and accuracy of data.

Pharmaceutical 52

Pharmaceutical Data Cleanse Metadata Medical 52

Edureka

AUGUST 2, 2023

Data Processing and Cleaning : Preprocessing and data cleaning are important steps since raw data frequently has errors, duplication, missing information, and inconsistencies. To make sure the data is precise and suitable for analysis, data processing analysts use methods including data cleansing, imputation, and normalisation.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Knowledge Hut

MAY 3, 2024

Spark Streaming Kafka Streams 1 Data received from live input data streams is Divided into Micro-batched for processing. processes per data stream(real real-time) 2 A separate processing Cluster is required No separate processing cluster is required. it's better for functions like row parsing, data cleansing, etc.

Kafka 98

Kafka Scala Java Amazon Web Services 98

ProjectPro

JANUARY 27, 2023

If you're wondering how the ETL process can drive your company to a new era of success, this blog will help you discover what use cases of ETL make it a critical component in many data management and analytic systems. Business Intelligence - ETL is a key component of BI systems for extracting and preparing data for analytics.

BI 52

BI ETL Tools Retail Healthcare 52

Knowledge Hut

DECEMBER 6, 2023

The educational requirement for the field of Data Science is preferably a B.E/B.Tech Data scientists are responsible for tasks such as data cleansing and organization, discovering useful data sources, analyzing massive amounts of data to find relevant patterns, and inventing algorithms.

Programming Language 52

Programming Language Data Cleanse Computer Science Education 52

Knowledge Hut

APRIL 23, 2024

Big Data Use Cases in Industries You can go through this section and explore big data applications across multiple industries. Clinical Decision Support: By analyzing vast amounts of patient data and offering in-the-moment insights and suggestions, use cases for big data in healthcare helps workers make well-informed judgments.

Big Data 52

Big Data Retail Recruitment Transportation 52