Remove Data Architect Remove Data Lake Remove Hadoop Remove NoSQL
article thumbnail

Data Architect: Role Description, Skills, Certifications and When to Hire

AltexSoft

This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. Hiring a well-skilled data architect can be very helpful for that purpose. What is a data architect? Let’s discuss and compare them to avoid misconceptions.

article thumbnail

Recap of Hadoop News for March

ProjectPro

News on Hadoop- March 2016 Hortonworks makes its core more stable for Hadoop users. PCWorld.com Hortonworks is going a step further in making Hadoop more reliable when it comes to enterprise adoption. Hortonworks Data Platform 2.4, Source: [link] ) Syncsort makes Hadoop and Spark available in native Mainframe.

Hadoop 52
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Top 16 Data Science Specializations of 2024 + Tips to Choose

Knowledge Hut

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

article thumbnail

100+ Big Data Interview Questions and Answers 2023

ProjectPro

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. Data Processing: This is the final step in deploying a big data model. Typically, data processing is done using frameworks such as Hadoop, Spark, MapReduce, Flink, and Pig, to mention a few.

article thumbnail

100+ Data Engineer Interview Questions and Answers for 2023

ProjectPro

Read more for a detailed comparison between data scientists and data engineers. How is a data architect different from a data engineer? Data architect Data engineers Data architects visualize and conceptualize data frameworks.

article thumbnail

Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

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. Amazon S3, Google Cloud Storage, Microsoft Azure Blob Storage), NoSQL databases (e.g.,

article thumbnail

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

AltexSoft

Built around a cloud data warehouse, data lake, or data lakehouse. Modern data stack tools are designed to integrate seamlessly with cloud data warehouses such as Redshift, Bigquery, and Snowflake, as well as data lakes or even the child of the first two — a data lakehouse.

IT 59