Cloudera

AUGUST 30, 2022

For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Towards Data Science ). Forrester ).

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

CIO Business Intelligence

NOVEMBER 28, 2023

With each game release and update, the amount of unstructured data being processed grows exponentially, Konoval says. This volume of data poses serious challenges in terms of storage and efficient processing,” he says. To address this problem RetroStyle Games invested in data lakes. Quality is job one.

Unstructured Data 130

Unstructured Data Data-driven Visualization Data Quality 130

CIO Business Intelligence

OCTOBER 2, 2024

With different people filtering and augmenting data, you need to trace who makes which changes and why, and you need to know which version of the data set was used to train a given model. And with all the data an enterprise has to manage, it’s essential to automate the processes of data collection, filtering, and categorization.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

Alation

MAY 16, 2023

Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible. Data Quality When using a data pipeline, data consistency, quality, and reliability are often greatly improved.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Ontotext

FEBRUARY 12, 2024

Domain teams should continually monitor for data errors with data validation checks and incorporate data lineage to track usage. Establish and enforce data governance by ensuring all data used is accurate, complete, and compliant with regulations. For instance, JPMorgan Chase & Co.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

Alation

FEBRUARY 13, 2020

Figure 1 illustrates the typical metadata subjects contained in a data catalog. Figure 1 – Data Catalog Metadata Subjects. Datasets are the files and tables that data workers need to find and access. They may reside in a data lake, warehouse, master data repository, or any other shared data resource.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Cloudera

AUGUST 4, 2021

Data governance used to be considered a “nice to have” function within an enterprise, but it didn’t receive serious attention until the sheer volume of business and personal data started taking off with the introduction of smartphones in the mid-2000s. Security: It must serve data throughout a system.

Data Governance 86

Data Governance Metadata Data-driven Enterprise 86

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

bridgei2i

MARCH 11, 2021

With improved data cataloging functionality, their systems can become responsive. It’ll become easier to store metadata (data lakes, warehouses, data quality systems, etc.) Over time, as more data is constantly fed to the responsive system, ML algorithms improve their efficiency. in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? 2) Always Remember Compliance Source: Unsplash There are now many different data privacy and security laws worldwide.

Data Governance 52

Data Governance Strategy Data Quality Data Collection 52

Alation

FEBRUARY 17, 2023

Some data seems more analytical, while other is operational (external facing). We recommend identifying the data sources and tables that need to be considered to be governed, establishing the governance owner & data quality details, and saving those details in the catalog. Where do you govern? Here’s an example.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Alation

MAY 16, 2023

Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible. Data Quality When using a data pipeline, data consistency, quality, and reliability are often greatly improved.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

FineReport

MARCH 24, 2024

Data Analyst Job Description: Major Tasks and Duties Data analysts collaborate with management to prioritize information needs, collect and interpret business-critical data, and report findings. Certified Analytics Professional (CAP) , providing advanced insights into converting data into actionable insights.

Statistics 52

Statistics Data mining Visualization Reporting 52

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

datapine

AUGUST 29, 2022

The new edition also explores artificial intelligence in more detail, covering topics such as Data Lakes and Data Sharing practices. 6) Lean Analytics: Use Data to Build a Better Startup Faster, by Alistair Croll and Benjamin Yoskovitz.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

CIO Business Intelligence

APRIL 23, 2025

Finally, refine and aggregate the clean data into insights that directly support key insurance functions like underwriting, risk analysis and regulatory reporting. Step 3: Data governance Maintain data quality. Enforce strict rules (schemas) to ensure all incoming data fits the expected format. Ensure reliability.

Insurance 109

Insurance Digital Transformation Data Quality Data Lake 109