phData: Data Engineering

NOVEMBER 1, 2024

VP of Architecture, Healthcare Industry Survey respondents selected data encryption as the most observed practice organizations are currently using to maintain data security. However, implementation in a large complex environment is difficult due to investment challenges and buy-in from the business.

Government 52

Government Data Governance Finance Metadata 52

Towards Data Science

DECEMBER 4, 2023

Anyways, I wasn’t paying enough attention during university classes, and today I’ll walk you through data layers using —  guess what  —  an example. Business Scenario & Data Architecture Imagine this: next year, a new team on the grid, Red Thunder Racing, will call us (yes, me and you) to set up their new data infrastructure.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Lake 98

Snowflake

DECEMBER 5, 2023

This lets them leverage the familiar development interface of a notebook while directing complex data preparation and feature engineering steps to run in Snowflake (rather than having to copy and manage copies of data inside their notebook instance).

AWS 119

AWS Amazon Web Services Government Cloud Computing 119

AltexSoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloudera

NOVEMBER 1, 2022

Translation: Government agencies — especially those under the Department of Defense (DoD) — have use cases that require data storage and analytic workloads to be maintained on premises to retain absolute control of data security, privacy, and cost predictability. . It’s here where the private cloud delivers.

Cloud 89

Cloud Government Cloud Computing Data Architecture 89

Cloudera

SEPTEMBER 12, 2022

Combining and analyzing both structured and unstructured data is a whole new challenge to come to grips with, let alone doing so across different infrastructures. Both obstacles can be overcome using modern data architectures, specifically data fabric and data lakehouse. Unified data fabric.

Unstructured Data 75

Unstructured Data Data Lake Data Architecture Data 75

Cloudera

OCTOBER 19, 2023

While navigating so many simultaneous data-dependent transformations, they must balance the need to level up their data management practices—accelerating the rate at which they ingest, manage, prepare, and analyze data—with that of governing this data.

Telecommunication 76

Telecommunication Data Architecture Government Architecture 76

phData: Data Engineering

FEBRUARY 21, 2025

Further, choosing the right CSP subscription model can help an organization meet its SLAs and data availability requirements. Security For most organizations, security is a top priority when establishing a data architecture. Organizations want to ensure that their data is secure both at rest and in-transit.

Cloud 52

Cloud Data Warehouse Amazon Web Services Data Ingestion 52

Cloudera

JUNE 6, 2024

While these are great proof points to demonstrate how business value can be driven by AI/ML, this was only made possible with trusted data. Trusted Data is the Foundation of AI According to a Cloudera survey, Data Architecture and Strategy in the AI Era , 57% of APAC organizations are at least early-stage adopters of AI.

Banking 83

Banking Data Lake Finance Data Governance 83

Cloudera

NOVEMBER 18, 2020

The technological linchpin of its digital transformation has been its Enterprise Data Architecture & Governance platform. It hosts over 150 big data analytics sandboxes across the region with over 200 users utilizing the sandbox for data discovery. Data Security & Governance.

Medical 123

Medical Banking Telecommunication Government 123

Cloudera

JUNE 14, 2021

How to optimize an enterprise data architecture with private cloud and multiple public cloud options? Figure 1: The Cloudera Data Platform offers hybrid cloud governance at its core: one data catalogue, one data lineage, and one data steward across multiple clouds, public and private.

Telecommunication 97

Telecommunication Cloud Finance Government 97

Cloudera

JANUARY 26, 2022

Modern, real-time businesses require accelerated cycles of innovation that are expensive and difficult to maintain with legacy data platforms. The hybrid cloud’s premise—two data architectures fused together—gives companies options to leverage those solutions and to address decision-making criteria, on a case-by-case basis. .

Cloud 87

Cloud Cloud Computing Hadoop Data Warehouse 87

Precisely

JANUARY 27, 2023

The challenge is that many business leaders still struggle to turn their data into tangible improvements in CX. According to Corinium , only 37% of organizations have a well-developed enterprise data architecture that enables high-quality, data-driven, and personalized CX.

High Quality Data 105

High Quality Data Data Governance Government Banking 105

Cloudera

APRIL 13, 2021

Its existing data architecture, however, wasn’t up for the gig. As the data ingestion rate of current business grew to multiple tens of gigabytes per day, the company saw the economic and functional limits of what could be done. The company turned to CDP to streamline migration of critical data workloads to the public cloud.

Cloud 78

Cloud Pharmaceutical Data Warehouse Medical 78

Cloudera

NOVEMBER 17, 2022

We needed a solution to manage our data at scale, to provide greater experiences to our customers. With Cloudera Data Platform, we aim to unlock value faster and offer consistent data security and governance to meet this goal. Aqeel Ahmed Jatoi, Lead – Architecture, Governance and Control, Habib Bank Limited.

Banking 85

Banking Management Data Lake Professional Services 85

Ascend.io

MAY 7, 2024

to bring its cutting-edge automation platform that revolutionizes modern data engineering. This partnership establishes a data efficiency center of excellence focused on AI & Automation tooling alongside best practices to ensure organizations maximize their data ROI. “Our collaboration with Ascend.io

Pipeline-centric 52

Pipeline-centric Data Cleanse Data Security Data Pipeline 52

Knowledge Hut

APRIL 20, 2023

The following are some of the key reasons why data governance is important: Ensuring data accuracy and consistency: Data governance helps to ensure that data is accurate, consistent, and trustworthy. This helps organisations make informed decisions based on reliable data.

Data Governance 59

Data Governance Government Data Cleanse Data Security 59

Cloudera

NOVEMBER 30, 2020

And then there are the added implications such heavy fines have for data security. As well as compliance within everyday operations, data breaches take on a whole new level of risk. . Corporations are obligated to ensure personal data is exposed in the right way to the right people.

Process 68

Process Designing Data Architecture Technology 68

Cloudera

SEPTEMBER 15, 2020

The main reason for this change is that this title better represents the move that our customers are making; away from acknowledging the ability to have data ‘anywhere’. Providing a single and consistent security and governance — In the world we find ourselves living in, it’s simply not acceptable to not know who has access to your data.

Cloud 67

Cloud Data Government Healthcare 67

Databand.ai

AUGUST 30, 2023

A DataOps architecture is the structural foundation that supports the implementation of DataOps principles within an organization. It encompasses the systems, tools, and processes that enable businesses to manage their data more efficiently and effectively. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Snowflake

AUGUST 21, 2023

With demonstrable success across a range of industries, organizations are increasingly pursuing cutting-edge data mesh architectures to enhance self-service data use. How, then, are modern data teams finding success with the data mesh?

Pipeline-centric 52

Pipeline-centric Architecture Government Data Architect 52

Knowledge Hut

OCTOBER 30, 2023

Develop a long-term vision for Power BI implementation and data analytics. Data Architecture and Design: Lead the design and development of complex data architectures, including data warehouses, data lakes, and data marts. Define data architecture standards and best practices.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

ProjectPro

FEBRUARY 1, 2017

Veikkaus has developed a modern data architecture by pulling data from both digital and offline betting channels. Primary hadoop vendors are getting serious about security but the major concern with big data security management is the lack of standardization.

Hadoop 52

Hadoop MongoDB Big Data Kafka 52

Mutt Data

SEPTEMBER 11, 2023

Mutt Data Is Climbing The Ranks of The Big Data Risk Management Industry Navigating big data risk assessment management is complex. Handling massive datasets demands advanced analytics expertise, AI integration, and data security assurance. Identifying subtle patterns and emerging risks requires skill.

Amazon Web Services 40

Amazon Web Services Google Cloud Big Data Consulting 40

Mutt Data

SEPTEMBER 11, 2023

Mutt Data Is Climbing The Ranks of The Big Data Risk Management Industry Navigating big data risk assessment management is complex. Handling massive datasets demands advanced analytics expertise, AI integration, and data security assurance. Identifying subtle patterns and emerging risks requires skill.

Amazon Web Services 40

Amazon Web Services Google Cloud Big Data Consulting 40

Monte Carlo

JANUARY 24, 2024

As data input channels and tech stacks become more complex and prolific, this manual approach to data governance just isn’t scalable. Plus, a growing number of companies are leveraging cloud-based, distributed data architectures like data mesh.

Data Governance 52

Data Governance Government Data Lake Data Architecture 52

Knowledge Hut

NOVEMBER 17, 2023

Azure Services You must be well-versed in a variety of Azure services, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Analysis Services, Azure Stream Analytics, and Azure Data Lake Storage, in order to succeed as an Azure Data Engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

MARCH 2, 2023

Data integrity is about maintaining the quality of data as it is stored, converted, transmitted, and displayed. Learn more about data integrity in our dedicated article. The vision provides a clear understanding of what the organization aims to achieve through its data governance efforts. The DAMA DMBOK wheel.

Data Governance 52

Data Governance Government Programming Healthcare 52

Cloudera

AUGUST 21, 2020

Organizations need to handle them in a transparent way because data hacking can happen at any point in the data-in-motion journey. Security needs to be treated at a mission-critical level and data security also needs to be a core part of a business’s strategic approach.

Banking 62

Banking Kafka Cloud Storage Government 62

RandomTrees

SEPTEMBER 27, 2024

Data Factory, Data Activator, Power BI, Synapse Real-Time Analytics, Synapse Data Engineering, Synapse Data Science, and Synapse Data Warehouse are some of them. With One Lake serving as a primary multi-cloud repository, Fabric is designed with an open, lake-centric architecture.

Database-centric 52

Database-centric Pipeline-centric IT BI 52

Knowledge Hut

DECEMBER 28, 2023

Hadoop can store data and run applications on cost-effective hardware clusters. Its data architecture is flexible, relevant, and schema-free. To learn more about this topic, explore our Big Data and Hadoop course. The data architecture must guarantee data security and enforce access control measures.

Hadoop 52

Hadoop Project Datasets Big Data 52

Knowledge Hut

MARCH 28, 2024

They work together with stakeholders to get business requirements and develop scalable and efficient data architectures. Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

NOVEMBER 28, 2023

This increased the data generation and the need for proper data storage requirements. A data architect is concerned with designing, creating, deploying, and managing a business entity's data architecture. Skills As the certification is significant, skills are the one that matters the most it.

Data Architect 52

Data Architect Data Science Certification Big Data 52

Ascend.io

SEPTEMBER 6, 2024

Here’s how predictive analytics can be effectively integrated into your data strategy: Integrating Predictive Analytics into Your Data Systems Infrastructure Readiness : Ensure your existing data architecture can support the computational demands of AI models.

Data Cleanse 52

Data Cleanse Data Workflow Data Pipeline Machine Learning 52

Knowledge Hut

MARCH 22, 2024

Cloud Data Architect A cloud data architect designs, builds and manages data solutions on cloud platforms like AWS, Azure, or GCP. They play a crucial role in ensuring data security, scalability, and performance, enabling organizations to leverage their data effectively for informed decision-making.

AWS 52

AWS Amazon Web Services Cloud Computing Computer Science 52

Precisely

JANUARY 22, 2024

The challenge is that many businesses struggle to turn their data into usable assets for CX applications. According to Corinium, only 37% of organizations have a well-developed enterprise data architecture that enables high-quality, data-driven, and personalized CX. It’s not that companies lack data about customers.

Data Integration 59

Data Integration Machine Learning High Quality Data Data Governance 59

Knowledge Hut

JUNE 23, 2023

Go for the best courses for Data Engineering and polish your big data engineer skills to take up the following responsibilities: You should have a systematic approach to creating and working on various data architectures necessary for storing, processing, and analyzing large amounts of data.

Data Engineering 52

Data Engineering Data Engineer Engineering NoSQL 52