Data Security NoSQL Structured Data 
Knowledge Hut
JULY 24, 2023
It is perfect for sectors like banking, finance, and healthcare that demand higher security and privacy since it offers a tamper-proof, unchangeable record of all transactions. Cloud migration has several benefits, including improved data accessibility, more straightforward data backup and disaster recovery, and lower infrastructure expenses.
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.
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Knowledge Hut
DECEMBER 26, 2023
The responsibilities of Data Analysts are to acquire massive amounts of data, visualize, transform, manage and process the data, and prepare data for business communications. In other words, they develop, maintain, and test Big Data solutions.
Knowledge Hut
DECEMBER 29, 2023
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.
Edureka
FEBRUARY 7, 2023
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. The main advantage of Azure Files over Azure Blobs is that it allows for folder-based data organisation and is SMB compliant, allowing for use as a file share.
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.
Knowledge Hut
APRIL 25, 2023
Strong programming skills: Data engineers should have a good grasp of programming languages like Python, Java, or Scala, which are commonly used in data engineering. Database management: Data engineers should be proficient in storing and managing data and working with different databases, including relational and NoSQL databases.
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