Monte Carlo

MARCH 12, 2025

Lesson 9: Using LLM clone models to keep data secure Understandably, many customers dont want their data exposed to foundational model providers like OpenAI and Anthropic, and they definitely dont want their data trained upon.

AWS 52

AWS Google Cloud Unstructured Data Coding 52

Cloudera

MAY 17, 2021

Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform. Beyond there being a number of choices each with very different strengths, the parameters for your decision have also changed.

Data Warehouse 90

Data Warehouse Cloud Government Metadata 90

Cloudera

JULY 26, 2021

Authorization: Define what users of internal / external organizations can access and do with the data in a fine-grained manner that ensures compliance with e.g., data obfuscation requirements introduced by industry and country specific standards for certain types of data assets such as PII.

Generalist 119

Generalist Telecommunication Healthcare Data Science 119

Cloudera

SEPTEMBER 12, 2022

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making.

Unstructured Data 75

Unstructured Data Data Lake Data Architecture Data 75

Snowflake

AUGUST 14, 2024

Cortex Analyst, built using Meta’s Llama and Mistral models, is a fully managed service that provides a conversational interface to interact with structured data in Snowflake. Historically, business users have primarily relied on BI dashboards and reports to answer their data questions.

BI 52

BI Analytics Application Government SQL 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

JANUARY 29, 2024

Outlier Detection: Identifying and managing outliers, which are data points that deviate significantly from the norm, to ensure accurate and meaningful analysis. Fraud Detection: Data wrangling can be instrumental in detecting corporate fraud by uncovering suspicious patterns and anomalies in financial data.

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52

RandomTrees

SEPTEMBER 17, 2024

Unified Governance: It offers a comprehensive governance framework by supporting notebooks, dashboards, files, machine learning models, and both organized and unstructured data. Security Model: With a familiar syntax, the security model simplifies authorization management by adhering to ANSI SQL standards.

Data Governance 52

Data Governance Government Metadata Machine Learning 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

JUNE 6, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Having the data engineering team lead the response to data quality is by far the most common pattern. It is deployed by about half of all organizations that use a modern data stack.

Data Governance 98

Data Governance Government Data Data Engineering 98

Towards Data Science

JUNE 8, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Photo by Luke Chesser on Unsplash Having the data engineering team lead the response to data quality is by far the most common pattern. Used with permission: source.

Data Governance 98

Data Governance Government Generalist Data Engineering 98

Knowledge Hut

JANUARY 30, 2024

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

ETL Tools 52

ETL Tools Database-centric Data Mining Raw Data 52

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. Statistician A Statistician has the responsibility of getting useful insights from data.

Data Science 97

Data Science BI Machine Learning Business Intelligence 97

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.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

Netflix Tech

MARCH 5, 2019

Challenges & Opportunities in the Infra Data Space Security Events Platform for Anomaly Detection How can we develop a complex event processing system to ingest semi-structured data predicated on schema contracts from hundreds of sources and transform it into event streams of structured data for downstream analysis?

Cloud 74

Cloud Building Amazon Web Services Metadata 74

Cloudera

NOVEMBER 15, 2024

Using Cloudera Data Flow and Cloudera Stream Processing, teams can filter, parse, normalize, and enrich log data in real time, ensuring that defenders are always working with clean, structured data that’s ready for advanced analytics.

Metadata 59

Metadata Unstructured Data Data Lake Government 59

Knowledge Hut

APRIL 25, 2024

It describes the actions people must take, the rules they must follow, and the technology that will support them throughout the data life cycle. Data security Data security is the technique of preventing digital data from being accessed by unauthorized parties, being corrupted, or being stolen at any point in its lifecycle.

Big Data 52

Big Data Data Analytics Manufacturing Retail 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

Monte Carlo

MAY 28, 2024

Common Tools Data Sources Identification with Apache NiFi : Automates data flow, handling structured and unstructured data. Used for identifying and cataloging data sources. Data Storage with Apache HBase : Provides scalable, high-performance storage for structured and semi-structured data.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Function Variety Big Data encompasses diverse data types, including structured, unstructured, and semi-structured data. It involves handling data from various sources such as text documents, images, videos, social media posts, and more.

Big Data 52

Big Data Datasets Data Analysis Media 52

Knowledge Hut

SEPTEMBER 26, 2023

You must be well versed in using the data dictionary tool in Power BI for this task. Advanced Data Modeling Skills Data modeling is the process of structuring data and defining the relationship between various data types to create a solid database structure.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

Edureka

FEBRUARY 9, 2023

Data engineering is a new and evolving field that will withstand the test of time and computing advances. Certified Azure Data Engineers are frequently hired by businesses to convert unstructured data into useful, structured data that data analysts and data scientists can use.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

Edureka

JULY 4, 2024

Advanced Security Features Security is top-notch with Synapse. You can be confident about your data security with features like column-level security, dynamic data masking, and automated threat detection. Databricks, on the other hand, takes a more modular approach.

Data Lake 40

Data Lake Pipeline-centric Data Warehouse ETL Tools 40

Knowledge Hut

OCTOBER 30, 2023

Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations. What Makes a Good Power BI Developer?

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Edureka

JULY 4, 2024

Contact support for Strategy Coach to pick the right solution and rely on numerous configuration options and performance settings to have your data securely and efficiently analyzed and processed. Amazon EMR creates cloud-based clusters running in accordance with selected configuration scripts.

AWS 52

AWS Amazon Web Services Hadoop Big Data 52

AltexSoft

NOVEMBER 10, 2021

The data in this case is checked against the pre-defined schema (internal database format) when being uploaded, which is known as the schema-on-write approach. Purpose-built, data warehouses allow for making complex queries on structured data via SQL (Structured Query Language) and getting results fast for business intelligence.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Knowledge Hut

APRIL 25, 2023

It provides a flexible data model that can handle different types of data, including unstructured and semi-structured data. Key features: Flexible data modeling High scalability Support for real-time analytics 4. Key features: Instant elasticity Support for semi-structured data Built-in data security 5.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Edureka

AUGUST 2, 2023

Data integration and transformation: Before analysis, data must frequently be translated into a standard format. Data processing analysts harmonise many data sources for integration into a single data repository by converting the data into a standardised structure.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Knowledge Hut

DECEMBER 29, 2023

Data Mining Data science field of study, data mining is the practice of applying certain approaches to data in order to get useful information from it, which may then be used by a company to make informed choices. It separates the hidden links and patterns in the data. Data mining's usefulness varies per sector.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Monte Carlo

FEBRUARY 15, 2023

Data Transformation Raw data ingested into a data warehouse may not be suitable for analysis. Data engineers use SQL, or tools like dbt, to transform data within the data warehouse. Data Security Data Warehouses achieve security in multiple ways. They need to be transformed.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

AltexSoft

MARCH 2, 2023

Data integrity is about maintaining the quality of data as it is stored, converted, transmitted, and displayed. Learn more about data integrity in our dedicated article. To design an effective data governance program, it’s crucial to choose an operational model that fits your business size and structure.

Data Governance 52

Data Governance Government Programming Healthcare 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 Machine Learning BI 64

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Silectis

JANUARY 3, 2021

Data lakes allow for more flexibility than a more rigid data warehouse. Data Lineage Data lineage describes the origin and changes to data over time Data Management Data management is the practice of collecting, maintaining, and utilizing data securely and effectively.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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 Data Storage 52

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.

Big Data 44

Big Data NoSQL Hadoop Data Lake 44

Knowledge Hut

DECEMBER 13, 2023

Micro Focus has rapidly amassed a robust portfolio of Big Data products in just a short amount of time. The Vertica Analytics Platform provides the fastest query processing on SQL Analytics, and Hadoop is built to manage a huge volume of structured data. VMware Big Data is simple to use, flexible, inexpensive, quick, and safe.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52