Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Data Visualization Graphic representation of a set or sets of data. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 1- Automating the Lakehouse's data intake.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

DECEMBER 29, 2023

In this role, they would help the Analytics team become ready to leverage both structured and unstructured data in their model creation processes. They construct pipelines to collect and transform data from many sources. It separates the hidden links and patterns in the data.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

OCTOBER 15, 2014

Does not have a dedicated metadata database. Makes use of exact variation of dedicated SQL DDL language by defining tables beforehand. Pig is SQL like but varies to a great extent. Directly leverages SQL and is easy to learn for database experts. Hive is similar to a SQL Interface in Hadoop.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

ProjectPro

JUNE 6, 2015

This industry interview series with Abed Ajraou focuses on the design and deployment of Solocal’s novel data architectural model using big data and Hadoop. BI is not a tool, a report or a database. BI is not like Oracle or SQL Server. The goal of BI is to create intelligence through Data. So what is BI?

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

ProjectPro

SEPTEMBER 11, 2015

Learning Hadoop will ensure that you can build a secure career in Big Data. Big Data is not going to go away. There will always be a place for RDBMS, ETL, EDW and BI for structured data. But at the pace and nature at which big data is growing, technologies like Hadoop will be very necessary to tackle this data.

Hadoop 52

Hadoop Java BI Big Data 52

ProjectPro

NOVEMBER 14, 2015

Data Migration RDBMSs were inefficient and failed to manage the growing demand for current data. This failure of relational database management systems triggered organizations to move their data from RDBMS to Hadoop. This data can be analysed using big data analytics to maximise revenue and profits.

Hadoop 52

Hadoop Project Big Data Healthcare 52

DareData

JANUARY 30, 2023

For data scientists, these skills are extremely helpful when it comes to manage and build more optimized data transformation processes, helping models achieve better speed and relability when set in production. Examples of relational databases include MySQL or Microsoft SQL Server.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

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.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 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.

Database 52

Database NoSQL Management 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

Knowledge Hut

SEPTEMBER 26, 2023

Microsoft Azure's Azure Synapse, formerly known as Azure SQL Data Warehouse, is a complete analytics offering. Designed to tackle the challenges of modern data management and analytics, Azure Synapse brings together the worlds of big data and data warehousing into a unified and seamlessly integrated platform.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

ProjectPro

JANUARY 19, 2022

Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 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

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

ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop AWS Relational Database 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

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. 4) What is Polybase?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., The complexity of the big data system increases with each data source.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

AltexSoft

JUNE 7, 2021

MapReduce performs batch processing only and doesn’t fit time-sensitive data or real-time analytics jobs. Data engineers who previously worked only with relational database management systems and SQL queries need training to take advantage of Hadoop. Cassandra excels at streaming data analysis.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JULY 27, 2021

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

MAY 14, 2021

And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. This data isn’t just about structured data that resides within relational databases as rows and columns.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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. The most common language for data analysis is SQL but barebone Hadoop doesn’t support it.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

NOVEMBER 10, 2021

So, unlike data warehouses, the lakehouse system can store and process lots of varied data at a lower cost, and unlike data lakes, that data can be managed and optimized for SQL performance. Data warehouse vs data lake vs data lakehouse: What’s the difference. Data warehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Rockset

SEPTEMBER 3, 2020

PostgreSQL is an open-source relational database that has been around for almost three decades. This capability allows PostgreSQL to be used as a document database as well. Unlike MongoDB, PostgreSQL also allows you to store data in a more traditional row and column arrangement. What Is PostgreSQL?

MongoDB 40

MongoDB PostgreSQL SQL Database 40

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

Knowledge Hut

JANUARY 11, 2024

It uses complex machine learning algorithms to build meaningful and structured data. Data Science can be described as a domain that applies advanced analytics, statistics and scientific principle for extracting valuable information and deriving valuable conclusions from structured or unstructured data.

Finance 93

Finance Data Science Programming Language Machine Learning 93

ProjectPro

DECEMBER 17, 2021

All this data is stored in a database that requires SQL-based queries for retrieval and transformations, making it essential for every data professional to learn SQL for data science and machine learning. Table of Contents Why SQL for Data Science? What is SQL? Why SQL for Data Science?

Data Science 52

Data Science SQL NoSQL Programming Language 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

ProjectPro

MAY 31, 2021

Data Description: For this project, you will create a sample database containing a table named ‘customer_detail.’ Language Used: SQL Packages/Libraries: Services: Amazon S3, Snowflake, SnowSQL, QuickSight Source Code: Snowflake Real-Time Data Warehouse Project for Beginners 3.

Big Data 52

Big Data Coding Project Hadoop 52