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

Knowledge Hut

JANUARY 30, 2024

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Edureka

FEBRUARY 7, 2023

In this case, the service provider creates a managed service that allows users to access these services on demand. Dynamic data masking serves several important functions in data security. It can be set up as a security policy on all SQL Databases in an Azure subscription.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Architecture 124

Architecture Metadata Government Kafka 124

Cloudera

SEPTEMBER 12, 2022

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. 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. Open data lakehouse.

Unstructured Data 74

Unstructured Data Data Lake Data Architecture Data 74

Monte Carlo

JUNE 6, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Having the data engineering team lead the response to data quality is by far the most common pattern. It is deployed by about half of all organizations that use a modern data stack.

Data Governance 98

Data Governance Government Data Data Engineering 98

Knowledge Hut

SEPTEMBER 26, 2023

The insights derived from the data in hand are then turned into impressive business intelligence visuals such as graphs or charts for the executive management to make strategic decisions. In this post, we will discuss the top power BI developer skills required to access Microsoft’s power business intelligence software.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

Knowledge Hut

DECEMBER 26, 2023

According to the Cybercrime Magazine, the global data storage is projected to be 200+ zettabytes (1 zettabyte = 10 12 gigabytes) by 2025, including the data stored on the cloud, personal devices, and public and private IT infrastructures. Statistician A Statistician has the responsibility of getting useful insights from data.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Towards Data Science

JUNE 8, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Photo by Luke Chesser on Unsplash Having the data engineering team lead the response to data quality is by far the most common pattern. Used with permission: source.

Data Governance 77

Data Governance Government Generalist Data Engineering 77

Monte Carlo

FEBRUARY 15, 2023

Data engineers use SQL, or tools like dbt, to transform data within the data warehouse. Data Security Data Warehouses achieve security in multiple ways. For example, some data warehouses: Can only be accessed using a private cloud. It also natively integrates with Apache Spark.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Knowledge Hut

OCTOBER 30, 2023

Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations. What Makes a Good Power BI Developer?

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Raw data store section.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

AltexSoft

MARCH 2, 2023

Data quality involves storing data in its correct and consistent form. Here’s a deep dive into data quality management and tools. Data availability is responsible for making data accessible to appropriate personnel within the system. Learn more about data integrity in our dedicated article.

Data Governance 52

Data Governance Government Healthcare Programming 52

Knowledge Hut

DECEMBER 13, 2023

Improving business decisions: Big Data provides businesses with the tools they need to make better decisions based on data rather than assumptions or gut feelings. However, all employees inside the organization must have access to the information required to enhance decision-making. Start your journey today!

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52

Knowledge Hut

NOVEMBER 17, 2023

Today, data is everything, and every technology runs around managing, storing, accessing, and processing this data. After the introduction of cloud computing, the need for managing expanding data is getting more critical. Below are the benefits of why data scientists across the globe highly adopt AWS.

AWS 52

AWS Data Science Certification Amazon Web Services 52

Cloudera

JULY 26, 2021

In fact, data product development introduces an additional requirement that wasn’t as relevant in the past as it is today: That of scalability in permissioning and authorization given the number and multitude of different roles of data constituents, both internal and external accessing a data product.

Generalist 117

Generalist Telecommunication Healthcare Data 117

Edureka

AUGUST 2, 2023

Data integration and transformation: Before analysis, data must frequently be translated into a standard format. Data processing analysts harmonise many data sources for integration into a single data repository by converting the data into a standardised structure.

Data Process 52

Data Process Process Data Cleanse Data Mining 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. Beyond there being a number of choices each with very different strengths, the parameters for your decision have also changed.

Data Warehouse 89

Data Warehouse Cloud Government Metadata 89

Knowledge Hut

APRIL 25, 2023

It provides a suite of tools for data preparation, modeling, and visualization, as well as collaboration and sharing. With Power BI, data engineers can easily create interactive reports and dashboards that can be accessed from anywhere, on any device. Google BigQuery is a fully-managed, serverless data warehouse service.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

AltexSoft

NOVEMBER 10, 2021

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. Traditional data warehouse platform architecture. Poor data quality, reliability, and integrity. Key features of a data lakehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Edureka

FEBRUARY 9, 2023

Azure Data Engineers Jobs – The Demand Azure Data Engineer Skills What does an Azure Data Engineer Do? Who is an Azure Data Engineer? Data is an organization’s most valuable asset, so making sure it can be accessed quickly and securely should be a top priority.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 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

Knowledge Hut

DECEMBER 29, 2023

The highlight feature of this platform is its potential to integrate semi-structured and structured data without using any third-party tools. Apache Hive It is a Hadoop-based data management and storage tool that allows data analytics through an SQL-like framework.

Data Engineering 40

Data Engineering Data Engineer Engineering BI 40

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64

Knowledge Hut

DECEMBER 29, 2023

Data Mining Data science field of study, data mining is the practice of applying certain approaches to data in order to get useful information from it, which may then be used by a company to make informed choices. It separates the hidden links and patterns in the data. Data mining's usefulness varies per sector.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

JANUARY 31, 2022

Snowflake also has data discovery features, allowing users to find and retrieve data more efficiently and rapidly. Snowflake Data Marketplace gives users rapid access to various third-party data sources. Moreover, numerous sources offer unique third-party data that is instantly accessible when needed.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Silectis

JANUARY 3, 2021

Data lakes allow for more flexibility than a more rigid data warehouse. Data Lineage Data lineage describes the origin and changes to data over time Data Management Data management is the practice of collecting, maintaining, and utilizing data securely and effectively.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

NOVEMBER 1, 2023

NER for structuring unstructured data NER plays a pivotal role in converting unstructured text into structured data. ” Once detected, the system can extract and input this data into the company’s management software for easier access and organization. Why use it?

Deep Learning 52

Deep Learning Machine Learning Datasets Algorithm 52

ProjectPro

JANUARY 19, 2022

Azure Data Engineer Job Description | Accenture Azure Certified Data Engineer Azure Data Engineer Certification Microsoft Azure Projects for Practice to Enhance Your Portfolio FAQs Who is an Azure Data Engineer? This is where the Azure Data Engineer enters the picture.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 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. Data orchestration.

Big Data 44

Big Data NoSQL Data Lake Hadoop 44

Netflix Tech

MARCH 5, 2019

Challenges & Opportunities in the Infra Data Space Security Events Platform for Anomaly Detection How can we develop a complex event processing system to ingest semi-structured data predicated on schema contracts from hundreds of sources and transform it into event streams of structured data for downstream analysis?

Cloud 73

Cloud Building Amazon Web Services Metadata 73

ProjectPro

JANUARY 24, 2023

With BigQuery, users can process and analyze petabytes of data in seconds and get insights from their data quickly and easily. Moreover, BigQuery offers a variety of features to help users quickly analyze and visualize their data. It provides powerful query capabilities for running SQL queries to access and analyze data.

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

NOVEMBER 15, 2021

When any particular project is open-sourced, it makes the source code accessible to anyone. The adaptability and technical superiority of such open-source big data projects make them stand out for community use. DataFrames are used by Spark SQL to accommodate structured and semi-structured data.

Big Data 52

Big Data Project Metadata Programming Language 52

phData: Data Engineering

JULY 18, 2023

The Ultimate Modern Data Stack Migration Guide phData Marketing July 18, 2023 This guide was co-written by a team of data experts, including Dakota Kelley, Ahmad Aburia, Sam Hall, and Sunny Yan. Imagine a world where all of your data is organized, easily accessible, and routinely leveraged to drive impactful outcomes.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

ProjectPro

MAY 13, 2016

For data scientists or data analysts, Hadoop and EDW are two different but great combinations that taste great when used together. A data warehouse makes the best use of relational and structured data whereas Hadoop excels in storing and managing unstructured data - which traditional data warehouses cannot handle.

Data Warehouse 40

Data Warehouse Hadoop Unstructured Data Big Data 40