Cloudera

FEBRUARY 15, 2024

Risk management and governance: Regulators are increasingly focusing on risk governance, risk sustainability, and the detection, mitigation, tracking, and remediation of threat actors. Financial institutions must demonstrate robust risk accountability and governance, as well as maintain consumer protections.

Insurance 85

Insurance Banking Data Architecture Data Ingestion 85

Snowflake

SEPTEMBER 7, 2023

Users can now easily connect to external network locations from their Snowpark code (UDFs/UDTFs and Stored Procedures) while maintaining high security and governance over their data. Partners and customers, like Airbyte and Snowflake’s internal data engineering team, are already benefiting from External Access in their workflows.

Amazon Web Services 118

Amazon Web Services AWS Government Python 118

Knowledge Hut

APRIL 23, 2024

With the advent of technology and the arrival of modern communications systems, computer science professionals worldwide realized big data size and value. As big data evolves and unravels more technology secrets, it might help users achieve ambitious targets. Top 10 Disadvantages of Big Data 1.

Big Data 52

Big Data Media Government Big Data Skills 52

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. It provides a flexible, scalable, and secure data infrastructure that can adapt to evolving business needs.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. It provides a flexible, scalable, and secure data infrastructure that can adapt to evolving business needs.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. It provides a flexible, scalable, and secure data infrastructure that can adapt to evolving business needs.

Data Management 52

Data Management Data Lake Management Data Governance 52

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Snowflake

NOVEMBER 22, 2023

“Before Snowflake, we couldn’t encrypt and ingest personally identifiable information (PII) or perform data subject requests (DSR),” explained Shandilya. Snowflake’s end-to-end encryption means we can apply governance in a way that’s appropriate for a critical infrastructure organization.”

IT 70

IT Data Architect Unstructured Data Programming Language 70

Cloudera

SEPTEMBER 12, 2022

Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. And second, for the data that is used, 80% is semi- or unstructured. Both obstacles can be overcome using modern data architectures, specifically data fabric and data lakehouse.

Unstructured Data 73

Unstructured Data Data Lake Data Architecture Data 73

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Data integration , on the other hand, happens later in the data management flow.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

APRIL 25, 2024

As businesses increasingly rely on intangible assets to create value, an efficient data management strategy is more important than ever. Data Integration Data integration is the process of combining information from several sources to give people a cohesive perspective.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Cloudera

JUNE 22, 2023

It ensures compliance with regulatory requirements while shifting non-sensitive data and workloads to the cloud. Its built-in intelligence automates common data management and data integration tasks, improves the overall effectiveness of data governance, and permits a holistic view of data across the cloud and on-premises environments.

Data Cleanse 65

Data Cleanse Data Governance Unstructured Data Cloud Storage 65

Knowledge Hut

MARCH 28, 2024

Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance. Develop data models, data governance policies, and data integration strategies. Familiarity with ETL tools and techniques for data integration.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Snowflake

NOVEMBER 29, 2023

While the former can be solved by tokenization strategies provided by external vendors, the latter mandates the need for patient-level data enrichment to be performed with sufficient guardrails to protect patient privacy, with an emphasis on auditability and lineage tracking.

Metadata 84

Metadata Healthcare Medical Data Storage 84

Precisely

MARCH 9, 2023

We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data. Precisely helps enterprises manage the integrity of their data.

Data Lake 59

Data Lake Data Warehouse Hadoop Raw Data 59

Towards Data Science

DECEMBER 4, 2023

We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Data Lake A data lake would serve as a repository for raw and unstructured data generated from various sources within the Formula 1 ecosystem: telemetry data from the cars (e.g.

Data Engineering 87

Data Engineering Data Engineer Engineering Data Lake 87

Precisely

MARCH 27, 2023

Changing consumer preferences, along with a shift in focus toward digital channels, was driving the need for new approaches to data integrity at the company. million, and optimized data management processes and data integrity across its GTM processes, generating additional recurring annual savings of $6.6

Food 52

Food Consulting Pharmaceutical Data Lake 52

AltexSoft

SEPTEMBER 23, 2021

A data hub is a central mediation point between various data sources and data consumers. It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. An ETL approach in the DW is considered slow, as it ships data in portions (batches.)

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

The Modern Data Company

MAY 10, 2023

Integration with existing systems: Ensure the solution can integrate seamlessly with your existing tools, applications, and infrastructure. Data governance and security: Evaluate the native security, data governance, and data quality management features. Needs to maintain data consistency and quality.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

DareData

JANUARY 30, 2023

As the field of data science and machine learning continues to evolve, it is increasingly evident that data engineering cannot be separated from it. Gone are the days when organizations could rely on models trained and stored in notebooks without any structure, governance, or testing.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Knowledge Hut

MARCH 7, 2024

Data analytics tools in big data includes a variety of tools that can be used to enhance the data analysis process. These tools include data analysis, data purification, data mining, data visualization, data integration, data storage, and management. Integrate.io - Integrate.io

Big Data 52

Big Data Data Analytics Data Mining MongoDB 52

The Modern Data Company

MAY 10, 2023

Integration with existing systems: Ensure the solution can integrate seamlessly with your existing tools, applications, and infrastructure. Data governance and security: Evaluate the native security, data governance, and data quality management features. Needs to maintain data consistency and quality.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

Integration with existing systems: Ensure the solution can integrate seamlessly with your existing tools, applications, and infrastructure. Data governance and security: Evaluate the native security, data governance, and data quality management features. Needs to maintain data consistency and quality.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Monte Carlo

NOVEMBER 6, 2023

They can range in terms of complexity, ease of use, and feature sets, but all are designed to help illuminate the dark corners of your data repositories, and are a critical component of your data governance practice. Here’s an overview of ten popular data discovery tools (in no particular order) that are available today.

Metadata 40

Metadata Unstructured Data Government Data Governance 40

Monte Carlo

FEBRUARY 21, 2023

A data fabric isn’t a standalone technology—it’s a data management architecture that leverages an integrated data layer atop underlying data in order to empower business leaders with real-time analytics and data-driven insights.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

A data fabric isn’t a standalone technology—it’s a data management architecture that leverages an integrated data layer atop underlying data in order to empower business leaders with real-time analytics and data-driven insights.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Ascend.io

NOVEMBER 21, 2023

More importantly, we will contextualize ELT in the current scenario, where data is perpetually in motion, and the boundaries of innovation are constantly being redrawn. Extract The initial stage of the ELT process is the extraction of data from various source systems. What Is ELT? So, what exactly is ELT?

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Monte Carlo

AUGUST 25, 2023

With pre-built functionalities and robust SQL support, data warehouses are tailor-made to enable swift, actionable querying for data analytics teams working primarily with structured data. This is particularly useful to data scientists and engineers as it provides more control over their calculations. Or maybe both.)

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g.,

Architecture 123

Architecture Metadata Government Kafka 123

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . QuerySurge – Continuously detect data issues in your delivery pipelines. Process Analytics. Meta-Orchestration .

Consulting 123

Consulting Machine Learning Data Science Data Pipeline 123

Cloudera

NOVEMBER 22, 2021

Open source frameworks such as Apache Impala, Apache Hive and Apache Spark offer a highly scalable programming model that is capable of processing massive volumes of structured and unstructured data by means of parallel execution on a large number of commodity computing nodes. . public, private, hybrid cloud)?

Government 91

Government Hadoop Data Security Data Warehouse 91

Knowledge Hut

JULY 26, 2023

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. However, Big Data encompasses unstructured data, including text documents, images, videos, social media feeds, and sensor data.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

Databand.ai

JULY 19, 2023

The extracted data is often raw and unstructured and may come in various formats such as text, images, audio, or video. The extraction process requires careful planning to ensure data integrity. It’s crucial to understand the source systems and their structure, as well as the type and quality of data they produce.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Knowledge Hut

JANUARY 30, 2024

Structured Data: Structured data sources, such as databases and spreadsheets, often require extraction to consolidate, transform, and make them suitable for analysis. Unstructured Data: Unstructured data, like free-form text, can be challenging to work with but holds valuable insights.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

AltexSoft

NOVEMBER 23, 2021

Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization.

Process 69

Process Data Lake Metadata Data Warehouse 69

Knowledge Hut

MARCH 27, 2024

is an all-in-one solution for businesses to connect their data and applications. It offers a cloud-based integration platform that helps businesses automate their data integration processes. Google Fusion Tables Google Fusion Tables is a web service that allows users to upload, merge, and visualize data tables.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52