Astera

NOVEMBER 30, 2023

Additionally, Data Vault 2.0 Data Vault 2.0 establishes comprehensive standards and guidelines for naming, modeling, loading, and documenting data. This ensures a foundation of quality, clarity, and manageability, making Data Vault 2.0 a comprehensive solution for modern data warehousing. Data Vault 2.0

Data Warehouse 52

Data Warehouse Healthcare Big Data Data Governance 52

The Data Administration Newsletter

AUGUST 3, 2021

Database standards are common practices and procedures that are documented and […]. Rigidly adhering to a standard, any standard, without being reasonable and using your ability to think through changing situations and circumstances is itself a bad standard.

Documentation 116

Documentation Data Quality Data Modelling Data Architecture 116

Astera

JUNE 6, 2023

Integration with Existing Infrastructure : Evaluate how well the tool integrates with your current infrastructure, including data storage systems and analytics platforms. Support and Documentation: Assess the level of support and availability of documentation from the tool’s vendor.

Data Warehouse 52

Data Warehouse Monitoring Real-time Data Documentation 52

Astera

DECEMBER 2, 2022

Reasons to Migrate Healthcare Data: There are various reasons why organizations seek a data migration solution. Modernizing Data Systems: Data architecture modernization is the most common reason for data migration. Stage 2: Cleansing Data. Some of those reasons are: 1.

Healthcare 52

Healthcare Documentation Data Quality Data Architecture 52

The Data Administration Newsletter

MAY 31, 2022

One very influential factor that can potentially undermine your data and document strategies is the natural and emotional reactions of people when things change. It is common to take great care in the selection and implementation of new technology.

Documentation 52

Documentation Change Management Data Architecture Big Data 52

Astera

MARCH 19, 2024

Data Standards and Metadata Management: Standardizing data formats, definitions, and naming conventions is crucial for ensuring consistency and interoperability across the organization. The program establishes processes for metadata management, including the documentation of data lineage, definitions, and usage policies.

Data Governance 52

Data Governance Government Data Quality Monitoring 52

Astera

MAY 6, 2024

Best For: Businesses that require a wide range of data mining algorithms and techniques and are working directly with data inside Oracle databases. Sisense Sisense is a data analytics platform emphasizing flexibility in handling diverse data architectures.

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

Tableau

SEPTEMBER 23, 2021

Low data discoverability: For example, Sales doesn’t know what data Marketing even has available, or vice versa—or the team simply can’t find the data when they need it. . Unclear change management process: There’s little or no formality around what happens when a data source changes. Data modeling.

Data Governance 91

Data Governance Government Data Quality Change Management 91

Domo

APRIL 20, 2022

On the front end, we work closely with subject matter experts,” said UPMC’s senior manager of data architecture and analytics. The finance people that know the finance data, for example. We make sure the data is checked and reliable. And then we use the certification process in Domo. “You

Embedded Analytics 98

Embedded Analytics Chief Data Officer Logistics Artificial Intelligence 98

Tableau

SEPTEMBER 23, 2021

Low data discoverability: For example, Sales doesn’t know what data Marketing even has available, or vice versa—or the team simply can’t find the data when they need it. . Unclear change management process: There’s little or no formality around what happens when a data source changes. Data modeling.

Data Governance 79

Data Governance Government Data Quality Change Management 79

Sisense

AUGUST 28, 2019

This functionality is especially pertinent in the case of mergers and acquisitions — you want to ensure your BI platform can support any future architecture that your company inherits along the way. But they come at the cost of true consumer flexibility — and your company’s ability to confidently invest in a cloud-agnostic data strategy.

Cloud Computing 73

Cloud Computing Data Architecture Data Modelling Documentation 73

Insight Software

JANUARY 17, 2022

Data Environment. The BI solutions you evaluate should be compatible with your current data environment, while at the same time have enough flexibility to meet future demands as your data architecture evolves. Customer success: Your BI vendor needs to be dedicated to your success.

Business Intelligence 52

Business Intelligence Business Intelligence User Experience Embedded Analytics 52

Astera

FEBRUARY 14, 2024

Establish a Robust Data Mapping Strategy: Create a comprehensive data mapping document that clearly outlines how data from the source aligns with Salesforce objects and fields. Use a data mapping tool to quickly map source and target data fields.

IBM Support 52

IBM Support IBM Maintenance IBM cost Data Quality 52

Argon Digital

FEBRUARY 9, 2023

These are only a few of the many questions that highlight the need for documentation when modeling even the simplest of organizational structures. However, the typical small business does not need complex data architecture and a large team to maintain service. What security concerns are there?

Finance 52

Finance Banking Vision Data Architecture 52

Insight Software

MARCH 4, 2024

However, this optimism often overlooks the reality of the situation: complex data architecture, mountains of manual tasks, and hidden inefficiencies in processing. Like an iceberg below the surface, these realities crash into expectations, leading to frustration and missed opportunities.

IBM cost 52

IBM cost IBM Support IBM Maintenance Supply Chain 52

Astera

FEBRUARY 14, 2024

Only 5% of businesses feel they have data management under control, while 77% of industry leaders consider growing volume of data one of the biggest challenges. Use automation tools to speed up and simplify the development and maintenance of the data vault. Automation Follow the data vault 2.0

Data Warehouse 52

Data Warehouse Data Modelling Agile Data Quality 52

Actian

JULY 31, 2019

As most manual processes utilizing paper moved to digital records management, content management systems emerged as a means to manage all the unstructured documents from knowledge workers or which the expanded functionality within ERP and personal computing systems autogenerated.

IBM Support 8

IBM Support Documentation IBM Maintenance Data Warehouse 8

Insight Software

JULY 28, 2023

Buying: With outsourced analytics solutions, there’s no need to worry about product maintenance, training, or documentation, since vendors extensively document their platforms. Make sure your data environment is good-to-go. Meaning, the solutions you think about should mesh with your current data architecture.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance IBM cost 52

Astera

DECEMBER 28, 2023

Error-handling and available documentation lack depth. Ab Initio Ab Initio is an enterprise-level self-service data platform offering a range of capabilities, including batch and real-time data integration, BI and analytics, automation, as well as data quality and governance.

IBM cost 52

IBM cost IBM Support IBM Maintenance Data Warehouse 52

Astera

DECEMBER 28, 2023

Error-handling and available documentation lack depth. Ab Initio Ab Initio is an enterprise-level self-service data platform offering a range of capabilities, including batch and real-time data integration, BI and analytics, automation, as well as data quality and governance.

IBM cost 52

IBM cost IBM Support IBM Maintenance Data Warehouse 52

Astera

OCTOBER 27, 2023

Download Trial Best Cloud Data Warehouse Solutions for Businesses Most cloud data warehousing solutions operate on the pay-as-you-go pricing model preferred by businesses, especially startups that are new to the world of data warehousing. Evaluate factors such as response times and the availability of support plans.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Sisense

SEPTEMBER 3, 2019

Modeling Your Data for Performance. Data architecture. The data landscape has changed significantly over the last two decades. The volume of data being created has increased, and the storage and computational resources needed to store and analyze that data has become cheaper and more widely available.

Data Warehouse 78

Data Warehouse Data Architecture Planning Big Data 78

Insight Software

MAY 1, 2023

Data Environment First off, the solutions you consider should be compatible with your current data architecture. We have outlined the requirements that most providers ask for: Data Sources Strategic Objective Use native connectivity optimized for the data source. Read carefully.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance IBM cost 52