Domo

JANUARY 30, 2024

To help people make timely data-driven decisions, your BI tool needs to be strong in several key product areas, such as: Data visualization Data source integration Warehousing Data transformation Data governance Machine learning and NLP But most tools aren’t strong in all six, or companies lack the resources to enable each component effectively.

Visualization 52

Visualization Documentation Data Governance Data Visualization 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

JANUARY 2, 2024

When data is organized and accessible, different departments can work cohesively, sharing insights and working towards common goals. Data Governance vs Data Management One of the key points to remember is that data governance and data management are not the same concepts—they are more different than similar.

Data Management 52

Data Management Data Warehouse Data Governance 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

APRIL 24, 2024

They gather, process, and analyze data from diverse sources. From handling modest data processing tasks to managing large and complex datasets, these tools bolster an organization’s data infrastructure. What are Data Aggregation Tools? The documentation and assistance videos can be unclear and overly technical.

IBM Support 52

IBM Support IBM Maintenance IBM cost E-Commerce 52

Sisense

JULY 6, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive.

Data Management 98

Data Management Data Architecture Data Governance Government 98

Astera

JULY 13, 2023

Unlike a data warehouse, a data lake does not limit the data types that can be stored, making it more flexible, but also more challenging to analyze. One of the key benefits of a data lake is that it can also store unstructured data, such as social media posts, emails, and documents.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40

Ntara

MAY 18, 2021

You can expect a constant back-and-forth as attributes are added and the data model—which both systems have to be aware of—is adjusted. Regardless of attribute type, the configuration in Salesforce should be done in a logical manner that is easy to understand (and well documented) so the attributes get assigned to the right products.

Innovation 52

Innovation Data Governance Customer Experience Customer Experience 52

Sisense

SEPTEMBER 12, 2019

We’ve been talking a lot recently about companies needing to use their data in order to stay in business in the future. We’ve even gone as far as saying that every company is a data company , whether they know it or not. Options include emails, meetings, PR, training, enablement, maybe even old-fashioned documentation. .

Government 81

Government Documentation Business Intelligence Business Intelligence 81

Sisense

NOVEMBER 5, 2021

Additionally, detailed documentation (almost like a data dictionary) for every data point gives users deeper understanding into how that data point was arrived at. Analytics are evolving: The first generation, which was very IT-driven, gave way to a more democratized, self-service paradigm.

Embedded Analytics 52

Embedded Analytics Data Warehouse Innovation Data Governance 52

The BAWorld

NOVEMBER 22, 2021

Data Modeling. Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Conceptual Data Model. Logical Data Model : It is an abstraction of CDM. Data Profiling.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

Data Pine

SEPTEMBER 29, 2022

Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business. These needs are then quantified into data models for acquisition and delivery. This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling.

Data Quality 96

Data Quality Monitoring Big Data Government 96