AltexSoft

MAY 12, 2023

Without a fixed schema, the data can vary in structure and organization. File systems, data lakes, and Big Data processing frameworks like Hadoop and Spark are often utilized for managing and analyzing unstructured data. You can’t just keep it in SQL databases, unlike structured data.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

DECEMBER 21, 2023

Data engineering involves a lot of technical skills like Python, Java, and SQL (Structured Query Language). For a data engineer career, you must have knowledge of data storage and processing technologies like Hadoop, Spark, and NoSQL databases. Knowledge of Hadoop, Spark, and Kafka.

Data Engineer 52

Data Engineer Data Engineering Engineering MongoDB 52

Knowledge Hut

MARCH 7, 2024

Data analytics tools in big data includes a variety of tools that can be used to enhance the data analysis process. These tools include data analysis, data purification, data mining, data visualization, data integration, data storage, and management.

Big Data 52

Big Data Data Analytics Data Mining MongoDB 52

ProjectPro

MARCH 19, 2015

NoSQL database can be referred to as structured storage which consists of relational database as the subset. NoSQL Database covers a swarm of multitude databases, each having a different kind of data storage model. NoSQL databases can also store and process data in real time - something that SQL is not capable of doing it.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

Cloud Academy

JANUARY 27, 2022

Microsoft SQL Server Document-oriented database: MongoDB (classified as NoSQL) The Basics of Data Management, Data Manipulation and Data Modeling This learning path focuses on common data formats and interfaces. Apache Kafka Amazon MSK and Kafka Under the Hood Apache Kafka is an open-source streaming platform.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineer 52

Data Engineer Data Engineering Engineering Google Cloud 52

Knowledge Hut

SEPTEMBER 6, 2023

Once the data is tailored to your requirements, it then should be stored in a warehouse system, where it can be easily used by applying queries. Some of the most popular database management tools in the industry are NoSql, MongoDB and oracle. You will become accustomed to challenges that you will face in the industry.

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

Knowledge Hut

NOVEMBER 7, 2023

Applications of Cloud Computing in Data Storage and Backup Many computer engineers are continually attempting to improve the process of data backup. Previously, customers stored data on a collection of drives or tapes, which took hours to collect and move to the backup location.

Cloud Computing 98

Cloud Computing Cloud Amazon Web Services Entertainment 98

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. How is Hadoop related to Big Data? Explain the difference between Hadoop and RDBMS.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Knowledge Hut

FEBRUARY 2, 2024

Skills Required HTML, CSS, JavaScript or Python for Backend programming, Databases such as SQL, MongoDB, Git version control, JavaScript frameworks, etc. Cloud Computing Course As more and more businesses from various fields are starting to rely on digital data storage and database management, there is an increased need for storage space.

Programming Language 98

Programming Language Amazon Web Services Java Cloud Computing 98

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 Engineer 52

Data Engineer Data Engineering Engineering Data Mining 52

Knowledge Hut

MARCH 27, 2024

Real-time analytics platforms in big data apply logic and math to gain faster insights into data, resulting in a more streamlined and informed decision-making process. Some open-source technology for big data analytics are : Hadoop. Listed below are the top and the most popular tools for big data analytics : 1.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

NOVEMBER 17, 2023

You must be able to create ETL pipelines using tools like Azure Data Factory and write custom code to extract and transform data if you want to succeed as an Azure Data Engineer. Big Data Technologies You must explore big data technologies such as Apache Spark, Hadoop, and related Azure services like Azure HDInsight.

Data Engineer 52

Data Engineer Data Engineering Engineering Scala 52

Ascend.io

SEPTEMBER 14, 2023

Use Case: Transforming monthly sales data to weekly averages import dask.dataframe as dd data = dd.read_csv('large_dataset.csv') mean_values = data.groupby('category').mean().compute() compute() Data Storage Python extends its mastery to data storage, boasting smooth integrations with both SQL and NoSQL databases.

Data Engineer 52

Data Engineer Data Engineering Python Engineering 52

Knowledge Hut

JUNE 23, 2023

You should be well-versed in Python and R, which are beneficial in various data-related operations. Apache Hadoop-based analytics to compute distributed processing and storage against datasets. Machine learning will link your work with data scientists, assisting them with statistical analysis and modeling. What is HDFS?

Data Engineer 52

Data Engineer Data Engineering Engineering NoSQL 52

AltexSoft

MARCH 14, 2023

Also, there are NoSQL databases that can be home to all sorts of data, including unstructured and semi-structured (images, PDF files, audio, JSON, etc.) Some popular databases are Postgres and MongoDB. But this distinction has been blurred with the era of cloud data warehouses. Data storage component in a modern data stack.

IT 59

IT Data Warehouse Data Governance Data Lake 59

ProjectPro

JANUARY 19, 2022

Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Good communication skills as a data engineer directly works with the different teams. These tools complement the knowledge of cloud computing as data engineers often implement codes that can handle large datasets over the cloud.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

ProjectPro

JANUARY 19, 2022

Here are some role-specific skills you should consider to become an Azure data engineer- Most data storage and processing systems use programming languages. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Who should take the certification exam?

Data Engineer 52

Data Engineer Data Engineering Engineering Data Storage 52

Edureka

JANUARY 18, 2024

Big Data Technologies Let’s examine big data, a technological wonder that changes information processing and opens up previously unexplored possibilities and insights. Hadoop Explore Big Data Technologies, including Hadoop, HDFS, and MapReduce, which enable efficient data management and parallel computation across large clusters.

Data Science 40

Data Science Deep Learning Machine Learning NoSQL 40

ProjectPro

JULY 30, 2021

There are many cloud computing job roles like Cloud Consultant, Cloud reliability engineer, cloud security engineer, cloud infrastructure engineer, cloud architect, data science engineer that one can make a career transition to. PaaS packages the platform for development and testing along with data, storage, and computing capability.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

ProjectPro

JULY 27, 2021

Below are some big data interview questions for data engineers based on the fundamental concepts of big data, such as data modeling, data analysis , data migration, data processing architecture, data storage, big data analytics, etc. Briefly define COSHH.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

AltexSoft

JUNE 26, 2023

Find sources of relevant data. Choose data collection methods and tools. Decide on a sufficient data amount. Set up data storage technology. Below, we’ll elaborate on each step one by one and share our experience of data collection. They can be accumulated in NoSQL databases like MongoDB or Cassandra.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Cloudera

DECEMBER 12, 2018

I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks. Greg Rahn: Toward the end of that eight-year stint, I saw this thing coming up called Hadoop and an engine called Hive. There’s MongoDB for document stores.

Data Warehouse 42

Data Warehouse Relational Database Hadoop Database 42

AltexSoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. The Hadoop toy. So the first secret to Hadoop’s success seems clear — it’s cute. What is Hadoop?

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

U-Next

AUGUST 10, 2022

Database Management: Understanding how to create and operate a data warehouse is a crucial skill. Data storage helps Data Engineers combine unorganized data that has been gathered from many resources. NoSQL databases are non-tabular, so they can be either a network or a record based on their data structure.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Science 52