Astera

APRIL 28, 2023

By AI taking care of low-level tasks, data engineers can focus on higher-level tasks such as designing data models and creating data visualizations. For instance, Coca-Cola uses AI-powered ETL tools to automate data integration tasks across its global supply chain to optimize procurement and sourcing processes.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

The Data Administration Newsletter

DECEMBER 20, 2022

Over the past few months, my team in Castlebridge and I have been working with clients delivering training to business and IT teams on data management skills like data governance, data quality management, data modelling, and metadata management.

Data Governance 52

Data Governance Government Data Quality Data Modelling 52

Dataversity

JUNE 19, 2023

In part one of this article, we discussed how data testing can specifically test a data object (e.g., table, column, metadata) at one particular point in the data pipeline.

Monitoring 130

Monitoring Data Modelling Data Quality Data Governance 130

The Data Administration Newsletter

OCTOBER 5, 2021

Doug has spoken many times at our Data Modeling Zone conferences over the years, and when I read the book, I can hear him talk in his distinct descriptive and conversational style. The Enrichment Game describes how to improve data quality and data useability […].

Data Modelling 52

Data Modelling Data Quality Data Management 52

Timo Elliott

DECEMBER 14, 2022

You lose the roots: the metadata, the hierarchies, the security, the business context of the data. It’s possible, but you have to recreate all that from scratch in the new environment, and that takes time and effort, and hugely increases the possibility of data quality and other governance problems. Business Content.

Innovation 244

Innovation Artificial Intelligence Data Warehouse Government 244

ElegantJ BI

SEPTEMBER 1, 2021

With a targeted self-serve data preparation tool, the midsized business can allow its business users to take on these tasks without the need for SQL skills, ETL or other programming language or data scientist skills.

Data Quality 130

Data Quality Visualization Data Modelling Agile 130

ElegantJ BI

SEPTEMBER 1, 2021

With a targeted self-serve data preparation tool, the midsized business can allow its business users to take on these tasks without the need for SQL skills, ETL or other programming language or data scientist skills.

Data Quality 130

Data Quality Visualization Data Modelling Agile 130

Astera

NOVEMBER 1, 2023

Data Integration: A data warehouse enables seamless integration of data from various systems and eliminates data silos and promotes interoperability and overall performance. Data-driven Finance with Astera Download Now Who Can Benefit from a Finance Data Warehouse?

Data Warehouse 52

Data Warehouse Finance Data Quality Banking 52

Astera

JANUARY 23, 2024

Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.

Agile 52

Agile Data Warehouse Data Quality Government 52

Astera

AUGUST 21, 2023

Introduced in 1996 by Ralph Kimball, a star schema is a multi-dimensional data modeling technique. It is the simplest schema type businesses use in data warehousing. This simple, denormalized structure makes it very efficient for querying data. Increased costs: Adding redundant data increases computing and storage costs.

Data Warehouse 52

Data Warehouse Data Modelling Data Quality Visualization 52

Sisense

APRIL 15, 2021

From data preparation , with attendant data quality assessment, to connecting to datasets and performing the analysis itself, helpful AI elements, invisibly integrated into the platform, make analysis smoother and more intuitive.

Artificial Intelligence 98

Artificial Intelligence Data Modelling Cloud Computing Data Discovery 98

Astera

JANUARY 18, 2024

Fivetran is also not an ideal solution if you are looking for a complete enterprise-grade data management solution as it doesn’t support data governance or offer advanced capabilities to improve data quality. All you need to do is just drag and drop the transformations in the data flow designer.

Data Warehouse 52

Data Warehouse Data Quality Data Management Government 52

Astera

NOVEMBER 14, 2023

Main Components of Astera’s Data Warehouse Builder With that said, almost any organization can deploy an agile data warehousing solution, provided that it has the right technology stack fueling the initiative.

Data Warehouse 52

Data Warehouse Agile Data Modelling Data Quality 52

Business Analysts

APRIL 5, 2023

Data analysis and modelling : AI projects require large amounts of data to train machine learning models. Business analysts can help organizations identify the data sources needed for AI projects, perform data analysis, and develop data models.

Artificial Intelligence 52

Artificial Intelligence Business Analysis Business Analysis Requirements Gathering 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

FEBRUARY 14, 2024

Data Mapping: Create a mapping between source and target data fields in Salesforce. Specify how data will be transformed and mapped during the migration process. Ensure alignment with Salesforce data models and consider any necessary data cleansing or enrichment. What about the rows with missing data?

IBM Support 52

IBM Support IBM Maintenance IBM cost Data Quality 52

Astera

JANUARY 25, 2024

Reverse ETL combined with data warehouse helps data analysts save time allowing them to focus on more complex tasks such as making sure their data is high quality, keeping it secure and private, and identifying the most important metrics to track. Data Models: These define the specific sets of data that need to be moved.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Sisense

JANUARY 14, 2021

VP of Business Intelligence Michael Hartmann describes the problem: “When an upstream data model change was introduced, it took a few days for us to notice that one of our Sisense charts was ‘broken.’ We believe this can help teams be more proactive and increase the data quality in their companies,” said Ivan.

E-Commerce 85

E-Commerce Business Intelligence Business Intelligence Data Modelling 85

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Data analysts in one organization might be called data scientists or statisticians in another.

Chief Data Officer 97

Chief Data Officer Finance Data Modelling Visualization 97

ElegantJ BI

SEPTEMBER 15, 2017

One of the crucial success factors for advanced analytics is to ensure that your data is clean and clear and that your users have a good understanding of the source of the data so that they can put results in perspective.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

ElegantJ BI

SEPTEMBER 15, 2017

One of the crucial success factors for advanced analytics is to ensure that your data is clean and clear and that your users have a good understanding of the source of the data so that they can put results in perspective.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

ElegantJ BI

SEPTEMBER 15, 2017

One of the crucial success factors for advanced analytics is to ensure that your data is clean and clear and that your users have a good understanding of the source of the data so that they can put results in perspective. Data Governance and Self-Serve Analytics Go Hand in Hand.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

Dataversity

MAY 1, 2023

Many organizations have mapped out the systems and applications of their data landscape. Many have modeled their data domains and key attributes. The remainder of this point of view will explain why connecting […] The post Connecting the Three Spheres of Data Management to Unlock Value appeared first on DATAVERSITY.

Data Management 244

Data Management Documentation Data Modelling Data Quality 244

Astera

JANUARY 23, 2023

See how we can help Best Practices of Healthcare Data Management To maximize the potential of implementing a healthcare data management system, hospitals and other healthcare facilities must collaborate to effectively manage, organize, safeguard, and transfer patient and provider information.

Data Management 52

Data Management IBM Maintenance Healthcare IBM cost 52

Smart Data Collective

JULY 9, 2023

By harmonising and standardising data through ETL, businesses can eliminate inconsistencies and achieve a single version of truth for analysis. Improved Data Quality Data quality is paramount when it comes to making accurate business decisions.

Data Warehouse 204

Data Warehouse Data Quality Data Analytics Data Analytics 204

Astera

MAY 25, 2023

Change management: Establish a standardized process for making changes to data sets. Data quality: Regularly check data for issues like inaccuracies, inconsistencies, and incompleteness. Have a plan in place to address any data quality issues discovered.

Big Data 40

Big Data Data Security Monitoring Data Quality 40

The Data Administration Newsletter

JANUARY 17, 2024

Eric Siegel’s “The AI Playbook” serves as a crucial guide, offering important insights for data professionals and their internal customers on effectively leveraging AI within business operations.

Data Modelling 122

Data Modelling Data Quality Data Governance Government 122

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

Astera

DECEMBER 21, 2022

Interestingly, even though multiple employees may be accessing the data warehouse simultaneously, data integrity is maintained in modern data warehouses so that organizations never have to worry about compromising their data quality for accessibility. Scalability and Elasticity.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

Tableau

JANUARY 27, 2021

In 2020, we released some of the most highly-anticipated features in Tableau, including dynamic parameters , new data modeling capabilities , multiple map layers and improved spatial support, predictive modeling functions , and Metrics. We continue to make Tableau more powerful, yet easier to use.

Business Intelligence 69

Business Intelligence Business Intelligence Government Visualization 69

Astera

MARCH 7, 2024

Primary purpose is to ensure that the data being tested is moving as it’s supposed to. Aims to ensure that all data follows the data model’s predefined rules. Checks for duplications in the loaded data. During data movement and transformation. It reports any invalid data.

Data Warehouse 52

Data Warehouse Data Quality Documentation Data Modelling 52

Dataversity

MARCH 22, 2021

This announcement is interesting and causes some of us in the tech industry to step back and consider many of the factors involved in providing data technology […]. The post Where Is the Data Technology Industry Headed? Click here to learn more about Heine Krog Iversen.

Planning 246

Planning Data Warehouse Data Quality Data Modelling 246

Tableau

JANUARY 27, 2021

In 2020, we released some of the most highly-anticipated features in Tableau, including dynamic parameters , new data modeling capabilities , multiple map layers and improved spatial support, predictive modeling functions , and Metrics. We continue to make Tableau more powerful, yet easier to use.

Business Intelligence 52

Business Intelligence Business Intelligence Government Visualization 52

Analysts Corner

JUNE 18, 2023

Python, Java, C#) Familiarity with data modeling and data warehousing concepts Understanding of data quality and data governance principles Experience with big data platforms and technologies (e.g., Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Dataversity

FEBRUARY 19, 2021

Enterprises are modernizing their data platforms and associated tool-sets to serve the fast needs of data practitioners, including data scientists, data analysts, business intelligence and reporting analysts, and self-service-embracing business and technology personnel. Click to learn more about author Tejasvi Addagada.

Business Intelligence 147

Business Intelligence Business Intelligence Data Modelling Data Governance 147

Dataversity

JULY 12, 2021

In my eight years as a Gartner analyst covering Master Data Management (MDM) and two years advising clients and prospects at a leading vendor, I have seen first-hand the importance of taking a multidomain approach to MDM. Click to learn more about author Bill O’Kane.

Master Data Management 130

Master Data Management Data Management Data Quality Data Governance 130