Cloudera

DECEMBER 11, 2020

The Data Security and Governance category, at the annual Data Impact Awards, has never been so important. Toolsets and strategies have had to shift to ensure controlled access to data. At the same time, the need to have a strong layer of security and governance is being highlighted.

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

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 66

Data Cleanse Data Governance Unstructured Data Cloud Storage 66

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. GDPR, HIPAA), and industry standards.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

APRIL 23, 2024

Sentiment Analysis and Natural Language Processing (NLP): AI and ML algorithms can process and analyze unstructured data, like text and speech, to better understand consumer sentiments. This entails constant surveillance, threat detection, and the adoption of strict security procedures all along the data lifecycle.

Big Data 52

Big Data Retail Recruitment Transportation 52

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 86

Data Engineering Data Engineer Engineering Data Lake 86

Knowledge Hut

JULY 24, 2023

Cloud migration has several benefits, including improved data accessibility, more straightforward data backup and disaster recovery, and lower infrastructure expenses. They are probably the best option for contemporary applications that need real-time data processing, great scalability, and flexibility.

Database 52

Database NoSQL Management Relational Database 52

Databand.ai

JULY 19, 2023

Unlike the traditional Extract, Transform, Load (ETL) process, where transformations are performed before the data is loaded into the data warehouse, in ELT, transformations are performed after the data is loaded. Implementing Strong Data Governance Measures Implementing strong data governance measures is crucial in ELT.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

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. . DVC — Open-source Version Control System for Machine Learning Projects … data version control.

Consulting 123

Consulting Machine Learning Data Science Data Pipeline 123

AltexSoft

FEBRUARY 11, 2023

If KPI goals are not met, a data architect recommends solutions (including new technologies) to improve the existing framework. Besides, it’s up to this specialist to guarantee compliance with laws, regulations, and standards related to data. This privacy law must be kept in mind when building data architecture.

Data Architect 87

Data Architect Certification Generalist Big Data 87

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

Knowledge Hut

JUNE 23, 2023

Data warehousing to aggregate unstructured data collected from multiple sources. Data architecture to tackle datasets and the relationship between processes and applications. Step 3 - How to Choose Project Management Courses for Data Engineer Learning Path? What’s the Demand for Data Engineers?

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Monte Carlo

APRIL 24, 2023

One weakness of the data lake architecture was the need to “bolt on” a data store such as Hive or Glue. This was largely overcome when Databricks announced their Unity Catalog feature which fully integrates those metastores along with other partnering data catalog and data security technologies.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Edureka

FEBRUARY 7, 2023

They should also be comfortable working with a variety of data sources and types and be able to design and implement data pipelines that can handle structured, semi-structured, and unstructured data.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

AltexSoft

AUGUST 29, 2023

Unstructured data sources. This category includes a diverse range of data types that do not have a predefined structure. Examples of unstructured data can range from sensor data in the industrial Internet of Things (IoT) applications, videos and audio streams, images, and social media content like tweets or Facebook posts.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

NOVEMBER 7, 2023

Every day, enormous amounts of data are collected from business endpoints, cloud apps, and the people who engage with them. Cloud computing enables enterprises to access massive amounts of organized and unstructured data in order to extract commercial value. This ensures the backup procedure and data security.

Cloud Computing 85

Cloud Computing Cloud Amazon Web Services Entertainment 85

Knowledge Hut

MARCH 26, 2024

Responsibilities: Define data architecture strategies and roadmaps to support business objectives and data initiatives. Design data models, schemas, and storage solutions for structured and unstructured data. Evaluate and recommend data management tools, database technologies, and analytics platforms.

Amazon Web Services 52

Amazon Web Services Google Cloud Computer Science AWS 52

Knowledge Hut

SEPTEMBER 6, 2023

Discover how these certifications can empower your career, from mastering cutting-edge database technologies to ensuring data security and compliance, providing you with a competitive edge in the digital age. Skills acquired : Core data concepts. Concept of structured, semi-structured, and unstructured data.

Certification 52

Certification Database MongoDB MySQL 52

Cloudera

SEPTEMBER 7, 2018

Moreover, this approach struggles to deal with the large volume and variety of data that must be analyzed and often correlated. Analyzing unstructured data sets such as text, audio and images are challenging, especially while determining illegal intent in communications. Requirements for data protection and governance .

Machine Learning 49

Machine Learning Unstructured Data Portfolio Relational Database 49

Databand.ai

DECEMBER 13, 2022

He is constantly seeking out knowledge and being excited by the challenge of learning something new in the data science space. His most passionate topics include MLOps, machine learning, data quality and data governance. You can also watch the video recording.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

ProjectPro

FEBRUARY 21, 2023

Data engineers and their skills play a crucial role in the success of an organization by making it easier for data scientists , data analysts , and decision-makers to access the data they need to do their jobs. Businesses rely on the knowledge and skills of data engineers to deliver scalable solutions to their clients.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

NOVEMBER 10, 2021

Traditional data warehouse platform architecture. Key data warehouse limitations: Inefficiency and high costs of traditional data warehouses in terms of continuously growing data volumes. Inability to handle unstructured data such as audio, video, text documents, and social media posts.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

NOVEMBER 23, 2021

Implementing data virtualization requires fewer resources and investments compared to building a separate consolidated store. Enhanced data security and governance. All enterprise data is available through a single virtual layer for different users and a variety of use cases. ETL in most cases is unnecessary.

Process 69

Process Data Lake Metadata Data Warehouse 69

Cloudera

OCTOBER 7, 2021

Infrastructure Environment: The infrastructure (including private cloud, public cloud or a combination of both) that hosts application logic and data. The Data Governance body designates a Data Product as the Authoritative Data Source (ADS) and its Data Publisher as the Authoritative Provisioning Point (APP).

Architecture 123

Architecture Metadata Government Kafka 123

AltexSoft

MARCH 30, 2023

This way, Delta Lake brings warehouse features to cloud object storage — an architecture for handling large amounts of unstructured data in the cloud. Source: The Data Team’s Guide to the Databricks Lakehouse Platform Integrating with Apache Spark and other analytics engines, Delta Lake supports both batch and stream data processing.

Scala 64

Scala Data Lake BI Google Cloud 64