Knowledge Hut

APRIL 23, 2024

Big data has revolutionized the world of data science altogether. With the help of big data analytics, we can gain insights from large datasets and reveal previously concealed patterns, trends, and correlations. Learn more about the 4 Vs of big data with examples by going for the Big Data certification online course.

Big Data 52

Big Data Media Datasets Unstructured Data 52

The Modern Data Company

JULY 18, 2023

It should address specific data challenges, such as improving operational efficiency, enhancing customer experience, or driving data-driven decision-making. Data Quality and Reliability Ensuring data quality is crucial for any data product.

Data Governance 52

Data Governance High Quality Data Government Data 52

The Modern Data Company

JULY 18, 2023

It should address specific data challenges, such as improving operational efficiency, enhancing customer experience, or driving data-driven decision-making. Data Quality and Reliability Ensuring data quality is crucial for any data product.

Data Governance 52

Data Governance High Quality Data Government Data 52

Databand.ai

AUGUST 30, 2023

Data Accuracy vs Data Integrity: Key Similarities Contribution to Data Quality Data accuracy and data integrity are both essential components of data quality. As mentioned earlier, data quality encompasses a range of attributes, including accuracy, consistency, completeness, and timeliness.

Data Integration 52

Data Integration Data Cleanse Data Validation Data Governance 52

Precisely

FEBRUARY 23, 2024

Their ability to generate business value is directly related to the quality of their data, however. Unless they have high-quality data, business users simply cannot deliver optimal results. The best data quality tools adapt easily as your company changes and grows.

Insurance 64

Insurance Data Validation Government High Quality Data 64

Monte Carlo

JULY 11, 2023

When crucial information is omitted or unavailable, the analysis or conclusions drawn from the data may be flawed or misleading. Inconsistent data: Inconsistencies within a dataset can indicate inaccuracies. This can include contradictory information or data points that do not align with established patterns or trends.

Data Cleanse 40

Data Cleanse Datasets Data Governance Government 40

Cloudera

MAY 18, 2022

Those algorithms require high quality data to deliver meaningful results. Data, whether structured, unstructured, or partly structured, comes in from various sources and needs to be sorted and analyzed with a data management platform. Bottom line.

Manufacturing 95

Manufacturing Retail High Quality Data Algorithm 95

Precisely

MARCH 14, 2023

New technologies are making it easier for customers to process increasingly large datasets more rapidly. If you happen to be a user of these products, you already know about the results that high-quality data produces: more and happier customers, lower costs and higher efficiency, and compliance with complex regulations – to name just a few.

Data Integration 52

Data Integration High Quality Data BI Data 52

Precisely

MARCH 23, 2023

The stakes are high and there isn’t a tolerance for error. Read Being transparent and having this type of information readily available is what builds confidence and trust in your brand and makes reporting and compliance processes more streamlined.

Data Integration 52

Data Integration Government High Quality Data Data 52

Databand.ai

JULY 5, 2023

Improved Collaboration Among Teams Data engineering teams frequently collaborate with other departments, such as analysts or scientists, who depend on accurate datasets for their tasks. Boosting Operational Efficiency A well-monitored data pipeline can significantly increase an organization’s operational efficiency.

Data Pipeline 52

Data Pipeline Data Lake Data Warehouse Datasets 52

DataKitchen

OCTOBER 2, 2023

Whether the Data Ingestion Team struggles with fragmented database ownership and volatile data environments or the End-to-End Data Product Team grapples with real-time data observability issues, the article provides actionable recommendations. ’ What’s a Data Journey?

Data Ingestion 40

Data Ingestion Data Government Datasets 40

Lyft Engineering

OCTOBER 3, 2023

High-quality data is necessary for the success of every data-driven company. It is now the norm for tech companies to have a well-developed data platform. This makes it easy for engineers to generate, transform, store, and analyze data at the petabyte scale.

Big Data 84

Big Data Metadata Data Warehouse Data 84

Databand.ai

AUGUST 30, 2023

Data quality monitoring refers to the assessment, measurement, and management of an organization’s data in terms of accuracy, consistency, and reliability. It utilizes various techniques to identify and resolve data quality issues, ensuring that high-quality data is used for business processes and decision-making.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

ProjectPro

FEBRUARY 21, 2023

GCP Data Engineer Certification The Google Cloud Certified Professional Data Engineer certification is ideal for data professionals whose jobs generally involve data governance, data handling, data processing, and performing a lot of feature engineering on data to prepare it for modeling.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

AUGUST 30, 2023

A passing test means you’ve improved the trustworthiness of your data. Schedule and automate You’ll need to run schema tests continuously to keep up with your ever-changing data. If your datasets are updated or refreshed daily, you’ll want to run your schema tests on a similar schedule. Also, remember data governance.

SQL 52

SQL Datasets Database High Quality Data 52

Precisely

JANUARY 16, 2024

To remain competitive, you must proactively and systematically pursue new ways to leverage data to your advantage. As the value of data reaches new highs, the fundamental rules that govern data-driven decision-making haven’t changed. To make good decisions, you need high-quality data.

Data Governance 69

Data Governance Government Metadata Data 69

Precisely

JANUARY 4, 2024

Data democratization is receiving more attention than ever, and data analytics is becoming a central element in compliance. Data governance is going mainstream as well, prompting companies to focus more attention on managing data quality at scale.

Data Governance 75

Data Governance Government Data Integration Data 75

Precisely

JANUARY 23, 2023

Data democratization is receiving more attention than ever, and data analytics is becoming a central element in compliance, including ESG reporting. Data governance is going mainstream as well, prompting companies to focus more attention on managing data quality at scale.

Data Governance 52

Data Governance Government Data Algorithm 52

Databand.ai

JANUARY 24, 2023

Supporting all of this requires a modern infrastructure and data architecture with appropriate governance. DataOps helps ensure organizations make decisions based on sound data. Enter DataOps. Who’s Involved in a DataOps Team? There are several roles that might be involved in a DataOps team in any given organization.

Retail 52

Retail Banking Government Manufacturing 52

Monte Carlo

MAY 17, 2023

Many times this is by freeing them from having to manually implement and maintain hundreds of data tests as was the case with Contentsquare and Gitlab. “We We had too many manual data checks by operations and data analysts,” said Otávio Bastos, former global data governance lead, Contentsquare. “It

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Many times this is by freeing them from having to manually implement and maintain hundreds of data tests as was the case with Contentsquare and Gitlab. “We We had too many manual data checks by operations and data analysts,” said Otávio Bastos, former global data governance lead, Contentsquare. “It

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52