Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Snowflake

NOVEMBER 30, 2023

It combines several migration approaches, methodologies and machine-first solution accelerators to help companies modernize their data and analytics estate to Snowflake. Daezmo has a suite of accelerators around data and process lineage identification, historical data migration, code conversion, and data validation and quality.

Data Warehouse 98

Data Warehouse Banking Data Cloud 98

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Smart DwH Mover helps in accelerating data warehouse migration.

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

RandomTrees

SEPTEMBER 6, 2020

The architecture is three layered: Database Storage: Snowflake has a mechanism to reorganize the data into its internal optimized, compressed and columnar format and stores this optimized data in cloud storage. This stage handles all the aspects of data storage like organization, file size, structure, compression, metadata, statistics.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Knowledge Hut

APRIL 20, 2023

It involves establishing a framework for data management that ensures data quality, privacy, security, and compliance with regulatory requirements. The mix of people, procedures, technologies, and systems ensures that the data within a company is reliable, safe, and simple for employees to access.

Data Governance 59

Data Governance Government Data Cleanse Data Security 59

Ascend.io

JULY 19, 2023

Process: Building Robust Systems from Data Governance to Product Publishing Just as a well-oiled machine needs precise processes, a successful data mesh needs to establish and adhere to processes regarding data governance, data curation, and data product publishing. Implement a publishing approval process.

Data Governance 40

Data Governance Government Metadata Data 40

Knowledge Hut

JUNE 30, 2023

DML statements provide the means to interact with the database, perform data analysis, generate reports, and modify data as per the application requirements. Relational databases offer a robust and flexible approach to data management, making them suitable for a wide range of applications.

MySQL 52

MySQL Medical Relational Database Healthcare 52

ProjectPro

JANUARY 31, 2023

Define Big Data and Explain the Seven Vs of Big Data. Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. And storing these metadata in RAM will become problematic.

Big Data 52

Big Data Hadoop AWS Relational Database 52

U-Next

SEPTEMBER 7, 2022

Maintaining communication with your staff, which necessitates correct employee data , is one approach to improve it. . What Is Employee Data Management? . Employee database management is a self-service system that allows employees to enter, update and assess their data. Improved Data Security and Sharing.

Data Management 52

Data Management Management Electronics Unstructured Data 52

ProjectPro

NOVEMBER 30, 2021

The data sources can be an RDBMS or some file formats like XLSX, CSV, JSON, etc., We need to extract data from all the sources and convert it into a single format for standardized processing. Validate data: Validating the data after extraction is essential to ensure it matches the expected range and rejects it if it does not.

Process 52

Process Data Pipeline Data Warehouse AWS 52

DataKitchen

SEPTEMBER 21, 2023

L1 is usually the raw, unprocessed data ingested directly from various sources; L2 is an intermediate layer featuring data that has undergone some form of transformation or cleaning; and L3 contains highly processed, optimized, and typically ready for analytics and decision-making processes.

Raw Data 67

Raw Data Data Business Intelligence High Quality Data 67

ProjectPro

AUGUST 21, 2015

Core components of a Hadoop application are- 1) Hadoop Common 2) HDFS 3) Hadoop MapReduce 4) YARN Data Access Components are - Pig and Hive Data Storage Component is - HBase Data Integration Components are - Apache Flume, Sqoop, Chukwa Data Management and Monitoring Components are - Ambari, Oozie and Zookeeper.

Hadoop 40

Hadoop Big Data Metadata Java 40

AltexSoft

NOVEMBER 23, 2021

As a result, data virtualization enabled the company to conduct advanced analytics and data science, contributing to the growth of the business. Global investment bank: Cost reduction with more scalable and effective data management. The platform quickened customer onboarding as well as product and service consulting.

Process 69

Process Data Lake Metadata Data Warehouse 69

DataKitchen

JANUARY 23, 2023

Data lineage and a data catalog are better together because they provide a more complete and accurate view of the data. Verification is checking that data is accurate, complete, and consistent with its specifications or documentation. Data lineage is static and often lags by weeks or months.

Data Governance 52

Data Governance Government Data Pipeline Data 52