Astera

SEPTEMBER 1, 2023

In addition, data warehousing helps improve other data management aspects, including: Data Security: Centralizing data in a data warehouse enables the implementation of robust security measures, ensuring that sensitive information is appropriately protected.

Data Warehouse 40

Data Warehouse Data Modelling Data Security Data Quality 40

Sisense

APRIL 16, 2019

We support embedding the full Sisense application, including the data modeling, analytics and administration areas, or embedding specific OEM dashboards and widgets using IFrames. Option 1: Shared ElastiCubes with row-based data security. Typically Best for: Tenants with identical data models and dashboard requirements.

Embedded Analytics 74

Embedded Analytics Data Modelling Data Security Change Management 74

Astera

JUNE 14, 2023

Ensuring data quality and consistency. Loading/Integration: Establishing a robust data storage system to store all the transformed data. Ensuring data security and privacy. Overcoming these challenges is crucial for utilizing external data effectively and gaining valuable insights.

Procurement 52

Procurement Data Security Retail Monitoring 52

Astera

APRIL 24, 2024

Many organizations face challenges with inaccurate, inconsistent, or outdated data affecting insights and decision-making processes. The data governance framework enhances the quality and reliability of the organization’s data. Assessing Data Security a.

Data Governance 52

Data Governance Government Data Architecture Data Quality 52

Astera

FEBRUARY 27, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

FEBRUARY 27, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Argon Digital

JUNE 7, 2023

Complex Data Model: Documentum employs a complex data model that can differ significantly from modern content management systems. Security and Compliance: Legacy systems might lack the robust security measures and compliance standards expected in modern software solutions.

Data Modelling 52

Data Modelling Planning Data Security 52

Insight Software

MARCH 13, 2024

While Microsoft Dynamics is a powerful platform for managing business processes and data, Dynamics AX users and Dynamics 365 Finance & Supply Chain Management (D365 F&SCM) users are only too aware of how difficult it can be to blend data across multiple sources in the Dynamics environment.

IBM Maintenance 52

IBM Maintenance IBM Support Supply Chain IBM Expert 52

Astera

NOVEMBER 30, 2023

With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, What is Data Vault 2.0? Data Vault 2.0

Data Warehouse 52

Data Warehouse Healthcare Big Data Data Governance 52

Astera

NOVEMBER 1, 2023

Faster Decision-Making: Quick access to comprehensive and reliable data in a data warehouse streamlines decision-making processes, which enables financial organizations to respond rapidly to market changes and customer needs.

Data Warehouse 52

Data Warehouse Finance Data Quality Banking 52

Tableau

MAY 11, 2022

If you are tasked with enforcing data management, you can have access to metrics on what data is being used, by whom, and at what frequency to make data source cleanup easier. . Connect and manage disparate data securely. The average enterprise has data in over 800 applications, and just 29% of them are connected.

Data Warehouse 95

Data Warehouse Government Artificial Intelligence Data Discovery 95

Tableau

MAY 11, 2022

If you are tasked with enforcing data management, you can have access to metrics on what data is being used, by whom, and at what frequency to make data source cleanup easier. . Connect and manage disparate data securely. The average enterprise has data in over 800 applications, and just 29% of them are connected.

Data Warehouse 93

Data Warehouse Government Artificial Intelligence Data Discovery 93

Astera

MAY 21, 2024

They’re the blueprint that defines how a database stores and organizes data, its components’ relationships, and its response to queries. Database schemas are vital for the data modeling process. Well-designed database schemas help you maintain data integrity and improve your database’s effectiveness.

Documentation 52

Documentation Data Modelling Visualization Data Requirement 52

Astera

JANUARY 2, 2024

Data Governance Data governance provides strategic oversight and a framework to ensure that data is treated as a valuable asset and managed in a way that aligns with organizational goals and industry best practices. It ensures data quality, consistency, and compliance with regulations.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Tableau

APRIL 18, 2022

Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Leverage semantic layers and physical layers to give you more options for combining data using schemas to fit your analysis. Data preparation.

Data Quality 99

Data Quality Government Artificial Intelligence Data Warehouse 99

Tableau

APRIL 18, 2022

Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Leverage semantic layers and physical layers to give you more options for combining data using schemas to fit your analysis. Data preparation.

Data Quality 97

Data Quality Government Artificial Intelligence Data Warehouse 97

Sisense

JUNE 26, 2019

We have often talked about the single-stack approach to business analytics, and with the complexity of enterprise data, this approach makes even more sense. . You want to make sure you have one place to bring in all your data and do your data modeling. Now Go Hybrid. This is the best of both worlds.

Data Warehouse 75

Data Warehouse Data Modelling Big Data Monitoring 75

Sisense

MARCH 18, 2019

For starters, we have data in multiple data sources and we didn’t want to refactor our databases and existing workflows just to launch our analytics solution. Added to that, each customer also has slight variations in their data model (variations coming from their single-tenant database) that had to be incorporated into the solution.

Embedded Analytics 71

Embedded Analytics Data Modelling Monitoring Logistics 71

Astera

APRIL 24, 2024

Best for: Data analysts and businesses needing a robust data aggregation tool. IBM Cloud Pak for Data IBM Cloud Pak for Data is an integrated data and AI platform that aids in removing data silos and improving data security and accessibility.

IBM Support 52

IBM Support IBM Maintenance IBM cost E-Commerce 52

Whizlabs

APRIL 24, 2021

Components of Power BI include: Power Query which is a tool which combines and enhances data from different sources. . Power Pivot is a data modelling tool offered by Power BI through which you can make models out of your base. . Power View is a tool that specializes in the visualization of your data.

Business Intelligence 98

Business Intelligence Business Intelligence Visualization Information Technology 98

Astera

JUNE 8, 2023

If you’re looking to store large amounts of data securely and access it quickly, then PostgreSQL and Oracle are both great options. Replication and High Availability: PostgreSQL provides built-in replication options for data redundancy and high availability. What Is Oracle?

Documentation 52

Documentation Cloud Computing Data Security Data Warehouse 52

Astera

JUNE 8, 2023

If you’re looking to store large amounts of data securely and access it quickly, then PostgreSQL and Oracle are both great options. Replication and High Availability: PostgreSQL provides built-in replication options for data redundancy and high availability. What Is Oracle?

Documentation 52

Documentation Cloud Computing Data Security Data Warehouse 52

Sisense

JANUARY 6, 2021

Nasdaq Investor Relations uses Sisense to infuse interactive reporting into its core offering, enabling customers to dissect and manipulate their data in innovative and impressive ways via white-label reports and dashboards. Horsepower under the hood.

Innovation 119

Innovation Visualization Data Visualization Product Management 119

Astera

JANUARY 24, 2024

If your Reverse ETL tool prioritizes sync reliability and robustness, you can rest easy knowing that your data will be synchronized regardless of any technical difficulties or other issues that may arise. Also look for data protection measures such as encryption for optimum security.

Data Warehouse 52

Data Warehouse Data Quality Data Management Data Security 52

Insight Software

SEPTEMBER 26, 2023

Their adept problem-solving skills instill confidence in data quality by showcasing the ability to promptly rectify issues. Data Security Strengthening: Users with proper training exhibit a heightened awareness of data security protocols and best practices.

IBM Maintenance 52

IBM Maintenance IBM Support IBM Expert Data Quality 52

Astera

MARCH 28, 2024

Establishing a data catalog is part of a broader data governance strategy, which includes: creating a business glossary, increasing data literacy across the company and data classification. Data Catalog vs. Data Dictionary A common confusion arises when data dictionaries come into the discussion.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Sisense

JULY 6, 2020

Data architecture creates instructions that guide you through the data collection, integration, and transformation processes, as well as data modeling. Data security is also a part of this field. Data Warehousing and BI represent the analytical core of an EDM system.

Data Management 98

Data Management Data Architecture Data Governance Government 98

Astera

DECEMBER 22, 2022

It’s one of the three core data types, along with structured and semi-structured formats. Examples of unstructured data include call logs, chat transcripts, contracts, and sensor data, as these datasets are not arranged according to a preset data model. This makes managing unstructured data difficult.

Data Quality 52

Data Quality Data Mining Data Warehouse Data Governance 52

Astera

JULY 13, 2023

By identifying and resolving inconsistencies, errors, and redundancies, data cleansing further enhances the integrity of the data. Data Mapping and Transformation: Data mapping bridges data elements from diverse sources.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40

Marutitech

NOVEMBER 13, 2020

Offers declarative data modeling. Offer various functionalities such as deployment settings, app preview, deployment logs, and data models. Robust data security and synchronization. And needless to say, it effortlessly connects with G Suite APIs. Features: Features a drag-and-drop user interface.

Visualization 98

Visualization User Experience Documentation Agile 98

Whizlabs

APRIL 26, 2021

Power Map- It is enabled for the users to create streamlined 3D visualizations of the obtained data or insights. Power Pivot- This app is dedicated to the creation of separate data models for making the data more insightful. Conclusion.

Visualization 52

Visualization Data Security Data Modelling Business Intelligence 52

Actian

OCTOBER 7, 2019

IT staff are challenged to implement them quickly, integrate them into enterprise data models and ensure the frictionless flow of information while simultaneously maintaining data security and integrity. Data hubs excel at the third-party integration challenge.

Data Warehouse 40

Data Warehouse Government Data Governance Agile 40

Astera

JANUARY 12, 2024

It was developed by Dan Linstedt and has gained popularity as a method for building scalable, adaptable, and maintainable data warehouses. Requires domain-specific governance frameworks to maintain data quality and standards. Data Quality Emphasizes strong data quality assurance practices.

Data Architecture 52

Data Architecture Data Warehouse Data Quality Government 52

Astera

MAY 13, 2024

Documenting the sensitivity analysis process to gain insights into the aggregated data’s reliability. Data Governance and Compliance Inadequate data governance and compliance procedures can risk your data security, quality, and integrity.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Astera

MAY 26, 2023

WHERE users.id = 1; Database Scalability: MongoDB supports horizontal scalability through sharding, which allows for distributing data across multiple servers. This allows for more fine-grained control over data access, which can be critical for data security and privacy.

E-Commerce 40

E-Commerce Documentation Data Security Data Quality 40

Domo

OCTOBER 22, 2021

Such an offering can also simplify and integrate data management on a massive scale—whether that data lives on premises or in cloud environments—and be used to develop an enterprise-wide data modeling process.

Data Warehouse 52

Data Warehouse Embedded Analytics Government Digital Transformation 52

Actian

OCTOBER 7, 2019

IT staff are challenged to implement them quickly, integrate them into enterprise data models and ensure the frictionless flow of information while simultaneously maintaining data security and integrity. Data hubs excel at the third-party integration challenge.

Data Warehouse 10

Data Warehouse Government Data Governance Agile 10