Grouparoo

NOVEMBER 29, 2021

Machine Data Equipment ranging from simple sensors to complex operational technology may generate information as a data source. This can vary from raw data extracted directly from the equipment or an intermediatory data source such as a data stream. It may be raw data, validated data, or big data.

Raw Data 40

Raw Data Big Data Relational Database Data Warehouse 40

Precisely

OCTOBER 5, 2023

According to the 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, 77% of data and analytics professionals say data-driven decision-making is the top goal of their data programs. That’s where data enrichment comes in.

Raw Data 67

Raw Data Insurance Datasets Telecommunication 67

Databand.ai

JULY 19, 2023

The Transform Phase During this phase, the data is prepared for analysis. This preparation can involve various operations such as cleaning, filtering, aggregating, and summarizing the data. The goal of the transformation is to convert the raw data into a format that’s easy to analyze and interpret.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

U-Next

MARCH 7, 2023

Taking data from sources and storing or processing it is known as data extraction. Define Data Wrangling The process of data wrangling involves cleaning, structuring, and enriching raw data to make it more useful for decision-making. Data is discovered, structured, cleaned, enriched, validated, and analyzed.

Data Mining 96

Data Mining Scala Government Data Governance 96

Precisely

MAY 3, 2023

Precisely CPO Anjan Kundavaram and Emily Washington, SVP of Product Management, will share exciting new Data Integrity Suite capabilities that support your end-to-end needs for accurate, consistent, and context-filled data. How can the power of data validation and enrichment transform your business? Join us to find out.

Data Integration 52

Data Integration AWS Government Data Governance 52

Databand.ai

AUGUST 30, 2023

Unified DataOps represents a fresh approach to managing and synchronizing data operations across several domains, including data engineering, data science, DevOps, and analytics. The goal of this strategy is to streamline the entire process of extracting insights from raw data by removing silos between teams and technologies.

Data Governance 40

Data Governance Data Cleanse Government Data Pipeline 40

dbt Developer Hub

SEPTEMBER 28, 2022

So let’s say that you have a business question, you have the raw data in your data warehouse , and you’ve got dbt up and running. The analyst will try to do as much discovery work up-front as possible, because it’s hard to predict exactly what you’ll find in the raw data. Or are you? Style Guide?).

Engineering 52

Engineering Raw Data Datasets BI 52

Precisely

JANUARY 11, 2024

Regardless of which approach is best for your business, it’s critical to keep governance and reliability intact throughout the process. Companies often try to combat these errors and improve data quality by defining hundreds of data validation rules – but that approach presents its own time-consuming challenges.

Technology 57

Technology Data Validation Raw Data Portfolio 57

ProjectPro

NOVEMBER 30, 2021

Now that we have understood how much significant role data plays, it opens the way to a set of more questions like How do we acquire or extract raw data from the source? How do we transform this data to get valuable insights from it? Where do we finally store or load the transformed data?

Process 52

Process Data Pipeline Data Warehouse AWS 52

Monte Carlo

MAY 31, 2023

Companies that leverage CRMs might mitigate risks related to broad domain access by implementing a framework that includes data collection controls, human-error checks, restricted raw data access, cybersecurity countermeasures, and frequent data back-ups.

Building 52

Building Data Validation Healthcare Data Integration 52

Precisely

JANUARY 8, 2024

Location intelligence provides a critical link that joins existing data elements with the geospatial context surrounding them. It’s worth noting, though, that to maximize the potential of location data, you need to address data quality issues first. Read Trend 3.

Insurance 62

Insurance Telecommunication Retail Data Integration 62

The Modern Data Company

AUGUST 13, 2024

Introduction to Data Products In today’s data-driven landscape, data products have become essential for maximizing the value of data. As organizations seek to leverage data more effectively, the focus has shifted from temporary datasets to well-defined, reusable data assets.

Raw Data 52

Raw Data Metadata Datasets Utilities 52