Ascend.io

FEBRUARY 28, 2024

Read More: AI Data Platform: Key Requirements for Fueling AI Initiatives How Data Engineering Enables AI Data engineering is the backbone of AI’s potential to transform industries , offering the essential infrastructure that powers AI algorithms.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Monte Carlo

FEBRUARY 26, 2024

A data catalog is a constantly updated inventory of the universe of data assets within an organization. It uses metadata to create a picture of the data, as well as the relationships between data assets of diverse sources, and the processing that takes place as data moves through systems.

Metadata 52

Metadata Government Data Data Governance 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

AltexSoft

AUGUST 22, 2022

The self-service functionally allows the entire organization to find relevant data faster and gain valuable insights. Support for different data types and use cases. A data fabric supports structured, unstructured, and semi-structured data whether it comes in real-time or generated in batches. Data catalog.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Cloudera

MAY 17, 2021

Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.

Data Warehouse 90

Data Warehouse Cloud Government Metadata 90

AltexSoft

NOVEMBER 10, 2021

In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Snowflake

JULY 10, 2023

Processing files in a Python UDF and Stored Procedure has piqued the interest of our data scientists and paves the way for automation of new, complex data pipelines.” Mike Tuck, Air Pollution Specialist Why unstructured data? Files read with a function or procedure are resolved with the function or procedure owner’s context.

Unstructured Data 40

Unstructured Data Python Process Scala 40

Monte Carlo

APRIL 1, 2021

As a result, data teams going the the lake or even lakehouse route often struggle to answer critical questions about their data such as: Where does my data live? Data discovery tools and platforms can help. They help data teams answer questions about where to look for data, what data represents, and how it can be used.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Monte Carlo

JULY 13, 2023

Utilizing a data permissions scanner and posture manager ensures that data engineers are informed about who has the potential to access data, which helps mitigate this risk. Automated processes scan all data stores and discover data, including semi-structured data such as JSON on a continual basis.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Ascend.io

JULY 19, 2023

Process: Building Robust Systems from Data Governance to Product Publishing Just as a well-oiled machine needs precise processes, a successful data mesh needs to establish and adhere to processes regarding data governance, data curation, and data product publishing. Promote cross-domain collaboration.

Data Governance 40

Data Governance Government Metadata Data 40

ProjectPro

FEBRUARY 16, 2023

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades. AWS Glue has a central metadata repository called the Glue catalog.

AWS 52

AWS Data Management ETL Tools Management 52

Snowflake

MARCH 30, 2023

Automation , because the same loader patterns are used for both and the same metadata tags are expected from both, meaning the applied date timestamp in the business vault will match up with the raw date timestamp where it came from. Data governance As a data management framework, feature stores must consider data privacy and data governance.

Engineering 84

Engineering Raw Data Data Science Machine Learning 84

AltexSoft

SEPTEMBER 23, 2021

A data hub serves as a single point of access for all data consumers, whether it be an application, a data scientist, or a business user. So, it also allows for managing data for various tasks, providing centralized governance and data flow control capabilities. Data hub architecture.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Precisely

OCTOBER 5, 2023

When we think about the big picture of data integrity – that’s data with maximum accuracy, consistency, and context – it becomes abundantly clear why data enrichment is one of its six key pillars (along with data integration, data observability, data quality, data governance, and location intelligence).

Raw Data 69

Raw Data Insurance Datasets Telecommunication 69

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. The difference between data warehouses, lakes, and marts.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Rockset

AUGUST 2, 2023

For one, the company decided to invest in an API Insights Lab where customers and partners across suppliers, carriers, governments and insurance companies could use maritime data as part of their internal systems and workflows. As a result, Windward wanted an underlying data stack that took an API first approach.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Monte Carlo

JULY 10, 2023

Data sampling If you’re working with large data sets where it’s impractical to evaluate every attribute or record, you can systematically sample your data set to estimate completeness. Be sure to use random sampling to select representative subsets of your data.

Data Collection 40

Data Collection Data Governance Government Data 40

AltexSoft

JULY 19, 2022

The HR team will manage all of this data and generate datasets to be consumed by other users in the company like the marketing team. They also own the governance of their domain. It’s easiest to understand the concept of a data mesh by looking at the core principles behind it which we’re going to uncover more extensively later on.

Architecture 52

Architecture Data Lake Medical Datasets 52

Monte Carlo

MARCH 14, 2023

Additionally, BlaBlaCar’s data leaders knew they needed to get ahead of governance to avoid creating new problems with siloed teams. In an effective data mesh, data governance tools need to be standardized,” said Kineret. And part of that is data observability and data quality. “And

Transportation 40

Transportation Government Data Engineering Data Engineer 40

AltexSoft

JULY 29, 2022

According to the latest report by Allied Market Research , the Big Data platform will see the biggest rise in adoption in telecommunication, healthcare, and government sectors. How HDFS master-slave structure works. If you divide it by 128 MB, you’ll have 8 data blocks. Source: Allied Market Research. Let’s see why.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

NOVEMBER 15, 2021

With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing. DataFrames are used by Spark SQL to accommodate structured and semi-structured data. Calcite has chosen to stay out of the data storage and processing business.

Big Data 52

Big Data Project Metadata Programming Language 52

Grouparoo

JANUARY 11, 2022

A data warehouse is a unified repository where data from diverse sources undergo aggregation and integration into a usable source of information. To achieve this, a data warehouse will require processes to gather and integrate data, manage data quality, create metadata, and support any regulatory compliance and governance procedures.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge.

Big Data 44

Big Data NoSQL Hadoop Data Lake 44

Towards Data Science

FEBRUARY 15, 2023

Data by itself has no value, it needs to be organized, standardized, and clean. Governance is needed. In this context, data management in an organization is a key point for the success of its projects involving data. One of the main aspects of correct data management is the definition of a data architecture.

Data Lake 76

Data Lake Data Warehouse Hadoop Architecture 76

ProjectPro

JANUARY 31, 2022

Several organizations can quickly transform, integrate, and analyze their data with Snowflake's Data Cloud. They can also design and run data apps and securely share, gather, and commercialize real-time data. Snowflake saves and manages data on the cloud using a shared-disk approach, making data management simple.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Snowflake

JANUARY 18, 2023

Snowflake’s Secure Data Sharing allows authorized organizations to exchange directly queryable data without copying it, and with the level of governance and masking expected by the industry. Snowflake also allows users to easily subset data for iterative analysis and bring compute power directly to the data.

Pharmaceutical 84

Pharmaceutical AWS Java Healthcare 84

Monte Carlo

JUNE 14, 2023

Data observability platforms reduce your data downtime up to 80% and make your data engineers 30% more time efficient by replacing static, cumbersome data testing with machine learning models that can help detect, resolve, and prevent data issues. Let the data drive the data pipeline architecture.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Cloudera

SEPTEMBER 6, 2018

The solution combines Cloudera Enterprise , the scalable distributed platform for big data, machine learning, and analytics, with riskCanvas , the financial crime software suite from Booz Allen Hamilton. It supports a variety of storage engines that can handle raw files, structured data (tables), and unstructured data.

Banking 40

Banking Machine Learning Big Data Scala 40

ProjectPro

OCTOBER 20, 2021

On that note, what is AI governance? AI Governance is a necessary evil. The four guideposts of AI Governance are as follows: Integrity The integrity and validity of the algorithm have to be justified by analyzing decision lineage and justification of what micro-decisions lead to the final output.

Machine Learning 52

Machine Learning Algorithm Data Science Government 52

AltexSoft

NOVEMBER 1, 2023

GPEs represent countries, cities, states, or any other regions with a defined boundary or governance. NER for structuring unstructured data NER plays a pivotal role in converting unstructured text into structured data.

Deep Learning 52

Deep Learning Machine Learning Datasets Algorithm 52

AltexSoft

OCTOBER 8, 2021

The prevailing part of users claim that it is quite easy to configure and manage data flows with Oracle’s graphical tools. Data profiling and cleansing. The platform’s main capabilities comprise data integration, data quality assurance, and data governance. Data profiling and cleansing.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

AUGUST 24, 2021

4) Event Data Analysis NYC Open Data is free public data published by New York City agencies and partners. This project is an opportunity for data enthusiasts to engage in the information produced and used by the New York City government. Google BigQuery receives the structured data from workers.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Confluent

AUGUST 29, 2019

Instead of storing tables and columns, Neo4j represents all data as a graph, meaning that the data is a set of nodes with labels and relationships. Nodes are like our data entities (in this example, we use Person ). This approach to structuring data is called the property graph model.

Kafka 55

Kafka Process Algorithm Cloud 55

Rockset

DECEMBER 22, 2020

We will also need to store this data in Elasticsearch. This becomes increasingly relevant when your queries may change frequently, when new features need to be implemented or when new data sources are introduced. He then went on to work for Capgemini where he helped the UK government move into the world of Big Data.

SQL 40

SQL Data MongoDB Building 40