Knowledge Hut

MARCH 28, 2024

Data Engineer Career: Overview Currently, with the enormous growth in the volume, variety, and veracity of data generated and the will of large firms to store and analyze their data, data management is a critical aspect of data science. That’s where data engineers are on the go.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

Data Ingestion 40

Data Ingestion Data Government Datasets 40

Data Engineering Podcast

OCTOBER 12, 2020

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it?

Business Intelligence 100

Business Intelligence BI Consulting Data Ingestion 100

phData: Data Engineering

SEPTEMBER 19, 2023

With many data modeling methodologies and processes available, choosing the right approach can be daunting. This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Ascend.io

JANUARY 10, 2024

Visual representation of Conway’s Law ( source ) Read More: The Chief AI Officer: Avoid The Trap of Conway’s Law Process: Ensuring Data Readiness The backbone of successful AI implementation is robust data management processes. AI models are only as good as the data they consume, making continuous data readiness crucial.

Data Pipeline 52

Data Pipeline Government Data Governance Raw Data 52

Precisely

SEPTEMBER 11, 2023

By 2025, 50% of data and analytics leaders will be using augmented MDM and active metadata to enhance their capabilities – demonstrating that beyond data quality, automation is also in demand for data governance, data catalog, and security solutions.

Metadata 52

Metadata Data Integration Datasets Data Analysis Tools 52

AltexSoft

AUGUST 29, 2023

If your organization fits into one of these categories and you’re considering implementing advanced data management and analytics solutions, keep reading to learn how data lakes work and how they can benefit your business. Real-time ingestion immediately brings data into the data lake as it is generated.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Snowflake

AUGUST 16, 2023

Data comes in a continuous manner, and often a separate architecture is required to handle streaming data. What remains challenging is how streaming data is brought together with batch data. That’s why we built Snowpipe Streaming, now generally available to handle row-set data ingestion.

Scala 52

Scala Transportation Kafka Data Lake 52

Edureka

FEBRUARY 7, 2023

An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Cloudera

MAY 9, 2019

Data readiness – These set of metrics help you measure if your organization is geared up to handle the sheer volume, variety and velocity of IoT data. It is meant for you to assess if you have thought through processes such as continuous data ingestion, enterprise data integration and data governance.

Manufacturing 53

Manufacturing Data Ingestion Architecture Data Governance 53

Monte Carlo

APRIL 24, 2023

We continuously hear data professionals describe the advantage of the Snowflake platform as “it just works.” Snowpipe and other features makes Snowflake’s inclusion in this top data lake vendors list a no-brainer. AWS is one of the most popular data lake vendors. A picture of their Lake Formation architecture.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Cloudera

FEBRUARY 16, 2022

SDX provides open metadata management and governance across each deployed environment by allowing organisations to catalogue, classify as well as control access to and manage all data assets. They define each stage from data ingest, feature engineering, model building, testing, deployment and validation.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

ProjectPro

FEBRUARY 21, 2023

Due to the enormous amount of data being generated and used in recent years, there is a high demand for data professionals, such as data engineers, who can perform tasks such as data management, data analysis, data preparation, etc. big data and ETL tools, etc.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Data Engineering Podcast

NOVEMBER 16, 2020

At Isima they decided to reimagine the entire ecosystem from the ground up and built a single unified platform to allow end-to-end self service workflows from data ingestion through to analysis. Immuta is an automated data governance solution that enables safe and easy data analytics in the cloud.

Data Management 100

Data Management Management BI Business Intelligence 100

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. Potential downsides of data lakes include governance and integration challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. Potential downsides of data lakes include governance and integration challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. Potential downsides of data lakes include governance and integration challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. These tools help organizations implement DataOps practices by providing a unified platform for data teams to collaborate, share, and manage their data assets.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Edureka

FEBRUARY 9, 2023

As the demand for data engineers grows, having a well-written resume that stands out from the crowd is critical. Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. It is also crucial to have experience with data ingestion and transformation.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Data Engineering Podcast

JUNE 19, 2022

In order to level up their value a new trend of active metadata is being implemented, allowing use cases like keeping BI reports up to date, auto-scaling your warehouses, and automated data governance. report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months.

Metadata 130

Metadata MongoDB Scala MySQL 130

DareData

JANUARY 30, 2023

Our goal is to help data scientists better manage their models deployments or work more effectively with their data engineering counterparts, ensuring their models are deployed and maintained in a robust and reliable way. AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS).

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 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. The principles emphasize machine-actionability (i.e.,

Metadata 84

Metadata Healthcare Medical Data Storage 84

Cloudera

DECEMBER 20, 2021

But balancing a strong layer of security and governance with easy access to data for all users is no easy task. Another option — a more rewarding one — is to include centralized data management, security, and governance into data projects from the start.

Government 86

Government Data Security Banking Metadata 86

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

Monte Carlo

NOVEMBER 14, 2023

However, leveraging a solution like Tabular , an Apache Iceberg managed table store that bills itself as a “headless data warehouse,” can help remove some of that data management overhead and streamline resource management. Limited data type support.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Data Engineering Weekly

NOVEMBER 13, 2022

Streaming and batch unified in a single platform No Airflow - orchestration inferred from the data $99 / TB of data ingested | transformations free Start Your 30 Day Trial Wealthfront: Event Tracking System at Wealthfront A robust event-tracking system is critical for an efficient data management platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

phData: Data Engineering

AUGUST 4, 2023

Database Storage The Snowflake architecture’s database storage layer organizes data into multiple tiny partitions, which are compressed and optimized internally. Snowflake stores and manages data in the cloud using a shared disk approach, which simplifies data management.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

Towards Data Science

JULY 24, 2023

A decade later, a considerable amount of innovation in the data management industry is revolving around how different data platforms are coupling or decoupling storage and compute (don’t worry I include examples in the next section). Take data governance for example.

Metadata 97

Metadata Data Warehouse Data Lake Data Science 97

Snowflake

MARCH 30, 2023

3EJHjvm Once a business need is defined and a minimal viable product ( MVP ) is scoped, the data management phase begins with: Data ingestion: Data is acquired, cleansed, and curated before it is transformed. ML workflow, ubr.to/3EJHjvm

Engineering 83

Engineering Raw Data Data Science Scala 83

Ascend.io

MARCH 14, 2023

Simply put, a data mesh is a platform architecture — a philosophy of sorts — that separates data into domains and defines the responsibilities of each. It provides a more distributed, decentralized, and resilient approach to data management. appeared first on Ascend.io.

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

Simply put, a data mesh is a platform architecture — a philosophy of sorts — that separates data into domains and defines the responsibilities of each. It provides a more distributed, decentralized, and resilient approach to data management. appeared first on Ascend.io.

Government 52

Government Architecture Data Lake Data 52

AltexSoft

JULY 29, 2022

To facilitate data ingestion, there are Apache Flume aggregating log data from multiple servers and Apache Sqoop designed to transport information between Hadoop and relational (SQL) databases. In September 2021 Snowflake announced the public preview of the unstructured data management functionality.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

NOVEMBER 15, 2021

Apache Zeppelin Source: Github Apache Zeppelin is a multi-purpose notebook that supports Data Ingestion, Data Discovery, Data Analytics , Data Visualization , and Data Collaboration. Apache Calcite Source: commons.wikimedia.org Apache Calcite is a full-stack category tool used for managing dynamic data.

Big Data 52

Big Data Project Metadata Programming Language 52

AltexSoft

MAY 12, 2023

Unstructured data refers to information that lacks a predefined format or organization. In contrast, big data refers to large volumes of structured and unstructured data that are challenging to process, store, and analyze using traditional data management tools. Invest in data governance.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Ascend.io

JULY 26, 2023

Data teams are tasked with the crucial responsibility of transforming raw data into valuable insights, a process that directly influences business outcomes. While some obstacles are specific to certain environments or business models, there are common challenges that many data teams confront.

Data Pipeline 52

Data Pipeline Data Governance Data Government 52

Monte Carlo

OCTOBER 5, 2023

So, in order for your company to uncover the true value of its data, you must take a structured approach to data quality. That’s where data quality standards come into play. Data quality standards for governance Data governance is the process of maintaining the availability, usability, privacy, and security of data.

Government 52

Government Data Governance Data Datasets 52

Monte Carlo

JULY 18, 2023

A decade later, a considerable amount of innovation in the data management industry is revolving around how different data platforms are coupling or decoupling storage and compute (don’t worry I include examples in the next section). Take data governance for example.

Metadata 52

Metadata Data Warehouse Data Lake Government 52