Remove Data Governance Remove Healthcare Remove Structured Data Remove Unstructured Data
article thumbnail

What is Data Extraction? Examples, Tools & Techniques

Knowledge Hut

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

article thumbnail

Veracity in Big Data: Why Accuracy Matters

Knowledge Hut

Variety: Variety represents the diverse range of data types and formats encountered in Big Data. Traditional data sources typically involve structured data, such as databases and spreadsheets. Handling this variety of data requires flexible data storage and processing methods.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

2020 Data Impact Award Winner Spotlight: Merck KGaA

Cloudera

Data security and governance champions – Merck KGaA. Based in Germany, Merck KGaA is one of the leading science and technology companies, operating across healthcare, life science, and performance materials business areas. It established a data governance framework within its enterprise data lake.

article thumbnail

Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Unstructured data sources.

article thumbnail

[O’Reilly Book] Chapter 1: Why Data Quality Deserves Attention Now

Monte Carlo

Alongside Lior Gavish, Barr set out to get to the root cause of the “data downtime” issue. Together, they interviewed hundreds of data teams about their biggest problems, and time and again, data quality sprang to the top of the list. We’ll take a closer look at variables that can impact your data next.

article thumbnail

What are the Features of Big Data Analytics

Knowledge Hut

When done correctly, data integration can enhance data quality, free up resources, lower IT costs, and stimulate creativity without significantly modifying current applications or data structures. Data Governance Data governance is the process of ensuring that data is trustworthy, accurate, available, and usable.

article thumbnail

Top ETL Use Cases for BI and Analytics:Real-World Examples

ProjectPro

Data Warehousing - ETL tools and processes can be leveraged to load data into a data warehouse for reporting and analysis. Master Data Management - ETL processes can be leveraged to maintain a single version of truth for key data entities by enforcing data governance, consolidation, and tracking data lineage.

BI 52