Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Monte Carlo

MAY 28, 2024

This involves connecting to multiple data sources, using extract, transform, load ( ETL ) processes to standardize the data, and using orchestration tools to manage the flow of data so that it’s continuously and reliably imported – and readily available for analysis and decision-making.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Knowledge Hut

DECEMBER 26, 2023

Certain roles like Data Scientists require a good knowledge of coding compared to other roles. Data Science also requires applying Machine Learning algorithms, which is why some knowledge of programming languages like Python, SQL, R, Java, or C/C++ is also required.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Striim

MAY 1, 2024

The sheer volume of data generated from the increasing package deliveries overwhelmed existing data management systems, underscoring a critical need for more advanced data handling capabilities. The absence of real-time data processing capabilities hindered UPS Capital’s risk management and rapid response efforts.

Google Cloud 52

Google Cloud Insurance Finance Machine Learning 52

Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data. Examples include Amazon DynamoDB and Google Cloud Datastore.

Database 52

Database NoSQL Management Relational Database 52

Edureka

AUGUST 2, 2023

R’s popularity in the data science community is also evident through its active community support and continuous development of new packages and techniques. SQL Structured Query Language, or SQL, is used to manage and work with relational databases. Data scientists use SQL to query, update, and manipulate data.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

Knowledge Hut

APRIL 23, 2024

Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data. Data warehousing offers several advantages. By structuring data in a predefined schema, data warehouses ensure data consistency and accuracy.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

APRIL 25, 2023

Database management: Data engineers should be proficient in storing and managing data and working with different databases, including relational and NoSQL databases. Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

MAY 2, 2024

It also supports a rich set of higher-level tools, including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming. In this article, we will cover the installation procedure of Apache Spark on the Ubuntu operating system.

Hadoop 52

Hadoop Java Scala Programming Language 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

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. They also encourage distributed computation for enhanced query performance and parallel data processing.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Data Engineering Weekly

JUNE 4, 2023

link] Uber: Spark Analysers: Catching Anti-Patterns In Spark Apps One of the challenges in commoditizing data processing engines like Spark is that it requires an expert user to understand and operate this system. Can we test SQL business logic during the development phase itself? Perhaps unit test the pipeline?

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

Edureka

FEBRUARY 7, 2023

Dynamic data masking serves several important functions in data security. It is possible to use Azure SQL Database, Azure SQL Managed Instance and Azure Synapse Analytics. It can be set up as a security policy on all SQL Databases in an Azure subscription. Users can change the level of masking to suit their needs.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Obviously, Big Data processing involves hundreds of computing units.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

U-Next

MARCH 1, 2023

Introduction Data Engineer is responsible for managing the flow of data to be used to make better business decisions. A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. What is AWS Kinesis?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Data Engineering Weekly

FEBRUARY 12, 2023

But compute needs will likely not change much over time; most analysis is done over recent data. Historical data processing is a rare event, where 99% of the computing happens over the last 24 hours of data. I believe the current data testing platforms can’t support the complex nature of data testing.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

Cloudera

APRIL 1, 2024

The following are key attributes of our platform that set Cloudera apart: Unlock the Value of Data While Accelerating Analytics and AI The data lakehouse revolutionizes the ability to unlock the power of data. We have embedded LLMs in our Hue interface so you can write SQL queries in English or any other language.

Cloud 104

Cloud Unstructured Data Metadata Datasets 104

Workfall

JULY 4, 2023

Reading Time: 8 minutes In the world of data engineering, a mighty tool called DBT (Data Build Tool) comes to the rescue of modern data workflows. Imagine a team of skilled data engineers on an exciting quest to transform raw data into a treasure trove of insights. In DBT, transformations are like these artisans.

Data Warehouse 69

Data Warehouse SQL PostgreSQL Database 69

ProjectPro

MARCH 19, 2015

RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data. As data processing requirements grow exponentially, NoSQL is a dynamic and cloud friendly approach to dynamically process unstructured data with ease.IT

NoSQL 49

NoSQL Big Data SQL Database-centric 49

Data Engineering Weekly

NOVEMBER 20, 2022

[link] The short YouTube video gives a nice overview of the Data Cards. We often think of AI/ ML as a complex data processing problem, but it doesn’t make any use until it is exposed to an end user or an application. The author narrates a few practical tips for creating success with people outside the data team.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

ProjectPro

JANUARY 31, 2023

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. Data Processing: This is the final step in deploying a big data model. How to avoid the same.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineers are engineers responsible for uncovering trends in data sets and building algorithms and data pipelines to make raw data beneficial for the organization. This job requires a handful of skills, starting from a strong foundation of SQL and programming languages like Python , Java , etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Snowflake

JULY 10, 2023

“California Air Resources Board has been exploring processing atmospheric data delivered from four different remote locations via instruments that produce netCDF files. Previously, working with these large and complex files would require a unique set of tools, creating data silos.

Unstructured Data 40

Unstructured Data Python Process Scala 40

Knowledge Hut

DECEMBER 21, 2023

HIVE Hive is an open-source data warehousing Hadoop tool that helps manage huge dataset files. Hive can run queries like SQL, known as HQL or Hive Query Language. Features: It uses queries that are similar to those of SQL. There are built-in functions used for data mining and other related works. Hive has high latency.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

ProjectPro

SEPTEMBER 9, 2021

Apache Hive and Apache Spark are the two popular Big Data tools available for complex data processing. To effectively utilize the Big Data tools, it is essential to understand the features and capabilities of the tools. Spark SQL, for instance, enables structured data processing with SQL.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

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

Snowflake

JULY 24, 2023

The company uses Snowflake’s Data Cloud to give business users quick and advanced data access using only basic SQL skills, meaning it has accelerated time-to-insight and decision-making. The company also uses external tables to directly access the semi-structured data within Snowflake.

Building 52

Building Engineering Finance Data Lake 52

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

AUGUST 11, 2021

Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data warehouses store highly transformed, structured data that is preprocessed and designed to serve a specific purpose. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Knowledge Hut

MARCH 27, 2024

Big data tools are used to perform predictive modeling, statistical algorithms and even what-if analyses. Some important big data processing platforms are: Microsoft Azure. Why Is Big Data Analytics Important? Let's check some of the best big data analytics tools and free big data analytics tools.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

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

Edureka

FEBRUARY 9, 2023

In this blog on “Azure data engineer skills”, you will discover the secrets to success in Azure data engineering with expert tips, tricks, and best practices Furthermore, a solid understanding of big data technologies such as Hadoop, Spark, and SQL Server is required.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

Knowledge Hut

DECEMBER 26, 2023

After carefully exploring what we mean when we say "big data," the book explores each phase of the big data lifecycle. With Tableau, which focuses on big data visualization , you can create scatter plots, histograms, bar, line, and pie charts. Key Benefits and Takeaways Learn the basics of big data with Spark.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Cloudera

SEPTEMBER 17, 2020

They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. Events or time-series data served by our real-time events or time-series data store solutions.

Unstructured Data 81

Unstructured Data Data Warehouse Pharmaceutical MySQL 81

Ascend.io

AUGUST 31, 2023

Shifting between these two patterns usually involves migration to new tooling to acquire data from sources. Transform in the Data Lake: Transformations in data lakes typically involve deep data engineering skills, using languages like Python, pySpark, and SQL, and data engines like Spark.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Grouparoo

DECEMBER 26, 2021

Relational Databases A relational database organizes data into tables that contain links between data elements that define their relationships. This allows quick access to information based on the connections between data elements. The relationships between each data element are the principal information of value for a business.

Database 52

Database NoSQL Relational Database Data Storage 52