Sisense

FEBRUARY 16, 2021

Every aspect of analytics is powered by a data model. A data model presents a “single source of truth” that all analytics queries are based on, from internal reports and insights embedded into applications to the data underlying AI algorithms and much more. Data modeling organizes and transforms data.

Data Modelling 52

Data Modelling Data Warehouse Banking Real-time Data 52

Analysts Corner

OCTOBER 30, 2024

Economic and business data often change due to external events, such as recessions, regulatory changes, or technological advances, affecting a model’s long-term reliability. Models built on pre-crisis data may become inaccurate, as historical relationships between features and outcomes change.

Data Quality 130

Data Quality Retail Finance Data Modelling 130

Dataversity

JULY 16, 2024

I was privileged to deliver a workshop at Enterprise Data World 2024. Publishing this review is a way to express my gratitude to the fantastic team at DATAVERSITY and Tony Shaw personally for organizing this prestigious live event.

Data Architecture 147

Data Architecture Data Governance Government Data Modelling 147

Astera

FEBRUARY 1, 2024

Data modeling is the process of structuring and organizing data so that it’s readable by machines and actionable for organizations. In this article, we’ll explore the concept of data modeling, including its importance, types , and best practices. What is a Data Model?

Data Modelling 40

Data Modelling Retail Documentation Visualization 40

Sisense

JANUARY 6, 2020

Best practice blends the application of advanced data models with the experience, intuition and knowledge of sales management, to deeply understand the sales pipeline. In this blog, we share some ideas of how to best use data to manage sales pipelines and have access to the fundamental data models that enable this process.

Data Modelling 91

Data Modelling Data Warehouse Logistics Customer Experience 91

Tableau

MARCH 19, 2024

“I liked working with numbers but I knew that accounting was not really for me, so I signed up for a course in data science which ultimately inspired me to get my Master’s degree in Data Modeling.” “A They create relevant posts on social media and inform their followers about upcoming events.”Asking

Data Visualization 129

Data Visualization Visualization Finance Data Modelling 129

Sisense

AUGUST 21, 2020

But that kind of thinking comes from the world we used to know, a world that was less volatile and more manageable, more influenced by the proximity ecosystem than by world events and climate. How exactly is all that data going to talk to each other and come together to provide the end-to-end analysis? Trend 6: Cloud is a given.

Data Modelling 112

Data Modelling Supply Chain Decision Modelling Visualization 112

Sisense

MARCH 30, 2020

Sisense Knowledge Graph is a powerful engine that was developed with over a decade’s worth of data, studying over 650 billion events that indicate organizational usage patterns. Report Manager (Premium Add-on) : Set up and share customized reports on a predefined schedule or triggered by events.

Artificial Intelligence 92

Artificial Intelligence Data Modelling Digital Business Intelligence 92

Sisense

APRIL 21, 2019

With a comprehensive, BI-focused data strategy, you and your stakeholders will know what your ideal data model should look like once all your data is moved over. BI-Focus and Your Data Infrastructure. What does all this have to do with my data model ?” you might be wondering. you might be wondering.

Data Modelling 72

Data Modelling Logistics Planning 72

Marutitech

DECEMBER 17, 2021

Simply put, predictive analytics is predicting future events and behavior using old data. Predicting future events gives organizations the advantage to understand their customers and their business with a better approach. You must be wondering what the different predictive models are? What is predictive data modeling?

Predictive Analytics 140

Predictive Analytics Data Mining Finance Data Analytics 140

Sisense

APRIL 10, 2020

Specific challenges involved with data related to the Coronavirus. Access to a reliable source of contagion data for a global event happening in real-time is not easy to discover. The major repositories that include data on public health issues or disease outbreaks can be accessed through an API. Data infrastructure.

Visualization 105

Visualization Data Modelling Healthcare Government 105

Passionate BA

SEPTEMBER 2, 2023

Yulia discusses the importance of accurate data modeling, pointing out missing entities, vague relationships, or overly complex designs. By addressing these common pitfalls, the article provides valuable guidance for domain and data modeling. Upcoming business analysis events 06.09, 6 PM CEST.

Business Analysis 130

Business Analysis Business Analysis Backlog Management Documentation 130

Sisense

JANUARY 15, 2021

Big data is now modeled and queried using advanced coding languages like SQL, Python, and R. And rather than answering prescriptive questions — something that BI teams excel at — data teams are able to model future events and understand how changing a past variable could have affected the present.

Skillset 75

Skillset Data Warehouse Data Modelling Business Intelligence 75

Inflexion Analytics

JULY 8, 2021

The resilience of supply chains has been tested in recent years by some catastrophic events and by political disruption to trade flows. For rarer, but higher-impact events the visualisations will inform the rapid recovery actions that need to be taken. [et_pb_section fb_built=”1″ _builder_version=”4.4.8″][et_pb_row

Supply Chain 52

Supply Chain Data Modelling Visualization Digital 52

Inflexion Analytics

OCTOBER 22, 2021

There has been political disruption to trade flows and disruption from catastrophic events, notably the Covid 19 pandemic. But data and analytics can also help them recover more quickly from the rarer, higher-impact events against which it is harder to hedge.

Supply Chain 52

Supply Chain Predictive Analytics Digital Data Modelling 52

Marutitech

APRIL 7, 2022

Predictive analytics is a new wave of data mining techniques and technologies which use historical data to predict future trends. Predictive Analytics allows businesses and investors to adjust their resources to take advantage of possible events and address issues before becoming problems. Data modeling.

Predictive Analytics 98

Predictive Analytics Data Modelling Data Mining Data Requirement 98

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. Free Ebook - The Essential Toolkit For Data Warehouse Automation Download

Data Warehouse 52

Data Warehouse Data Modelling Data Quality Visualization 52

Sisense

JULY 14, 2019

Disaster Recovery: deals with how vital systems are backed up so that if they are damaged or destroyed, code and vital data is recoverable. Incident Management: provides an action plan in case of a breach or other security event. Does your data model encompass all the datasets it needs to in order to drive value for your users?

Data Security 75

Data Security Data Modelling Documentation Cybersecurity 75

Monday

MAY 28, 2021

A business process is the logical sequence of events that lead to a particular outcome relevant to your organization. A process includes all the activities or tasks in a chain of events that accomplishes something. Some of the most popular structural diagrams include: Class diagram: mainly used for data modeling in a system.

Process Modelling 103

Process Modelling UML Visualization Project Management 103

Sisense

MAY 31, 2020

Sisense is delivering a beautiful front-end experience, powerful and flexible data modeling, and the opportunity to integrate at a very deep level.” ” Chris Wallingford, Director of Business Intelligence, Tessitura Network.

Data Warehouse 98

Data Warehouse Innovation Predictive Analytics Vision 98

Sisense

AUGUST 6, 2020

When building your data model, it’s vital to avoid both underfitting and overfitting. Although AI product managers may not be involved at the level of algorithm development, they can benefit from recognizing the symptoms of overfitting in the behavior of the model under development. The perfect fit.

Product Management 95

Product Management Product Management Customer Experience Customer Experience 95

Watermark Learning

JUNE 15, 2021

A variety of models can be used to show scope, including context diagrams, features in/out lists, use case diagrams, high-level data flow diagrams, and business processes. Data models. policies, calculations, sequence of events, limits, and business decisions).

Process Modelling 52

Process Modelling Project Management Data Modelling Visualization 52

Sisense

AUGUST 14, 2020

In the case of a stock trading AI, for example, product managers are now aware that the data required for the AI algorithm must include human emotion training data for sentiment analysis. It follows then that data scientists are suddenly integral to building embedded AI components.

Healthcare 98

Healthcare Cybersecurity Predictive Analytics Artificial Intelligence 98

Watermark Learning

OCTOBER 3, 2023

To support your work as a Business Analyst and for a certification exam, review these top modeling techniques: (Note to author – I added some definition around each one, so they knew what they were) Scope Modeling – visually describes what is in and out of scope of the focus area – e.g., solution, stakeholders, department, etc.

Process Modelling 86

Process Modelling Business Analysis Business Analysis Visualization 86

Tableau

SEPTEMBER 23, 2021

This enables employees to see data details like definitions and formulas, lineage and ownership information, as well as important data quality notifications, from certification status to events, like if a data source refresh failed and the information isn’t up to date. Data modeling. Data migration .

Data Governance 101

Data Governance Government Data Quality Change Management 101

Argon Digital

AUGUST 4, 2022

Creating a Business Data Diagram. I found the exercise of creating a Data Flow Diagram for a block walk/canvass so interesting that I decided to play with the same use case to create another data model, the Business Data Diagram (BDD). The BDD is one of the most important and useful models we use.

Banking 52

Banking Documentation Visualization Data Modelling 52

Argon Digital

AUGUST 4, 2022

I found the exercise of creating a Data Flow Diagram for a block walk/canvass so interesting that I decided to play with the same use case to create another data model, the Business Data Diagram (BDD). The BDD is one of the most important and useful models we use.

Banking 52

Banking Documentation Visualization Data Modelling 52

Actian

FEBRUARY 25, 2020

These cloud services leverage cloud-native architectures that are often highly distributed, leverage parallel processing, involve non-relational data models, and can be spun up or shut down in a matter of seconds. Events and data are evaluated, leading to dynamic workflows emerging based upon the needs of the individual transaction.

Data Warehouse 40

Data Warehouse Data Management Data Modelling Monitoring 40

Tableau

SEPTEMBER 23, 2021

This enables employees to see data details like definitions and formulas, lineage and ownership information, as well as important data quality notifications, from certification status to events, like if a data source refresh failed and the information isn’t up to date. Data modeling. Data migration .

Data Governance 97

Data Governance Government Data Quality Change Management 97

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

Whizlabs

APRIL 19, 2021

Michelle Bailey – GVP/GM & IDC Research Fellow at IDC, Speaker at Leading Industry Events. Michelle has more than 20 years of experience in the field of research in statistics, data analytics, consulting and market research. She is a frequent speaker at Leading Industry Events. Follow Chelsea L.

Cloud Computing 145

Cloud Computing IBM Support IBM Maintenance IBM cost 145

Domo

AUGUST 4, 2023

“The ShortLists reflect the vendors that our network of buy-side clients value the most, offering capabilities such as: data integration and preparation, data storytelling, dashboarding and reporting, security, access control, governance, data cataloging, data modeling, and data management.

Embedded Analytics 52

Embedded Analytics Business Intelligence Business Intelligence Digital Transformation 52

Astera

FEBRUARY 28, 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 23, 2024

It happens due to redundancy, duplications, and inconsistencies within datasets and is a sign of poor-quality data. Unhealthy data also complicates the backup and recovery processes, as finding and restoring accurate data becomes challenging in the event of data loss.

Data Quality 52

Data Quality Monitoring Data Modelling Data Warehouse 52

Astera

SEPTEMBER 20, 2024

Data is distributed across these centers to ensure redundancy and maintain high availability. Strategically located data centers worldwide minimize latency and ensure reliable access to data, even in the event of localized disruptions. There are several types of NoSQL databases, including document stores (e.g.,

Data Warehouse 40

Data Warehouse Cloud Computing E-Commerce Documentation 40

Astera

JANUARY 23, 2023

Prescriptive analytics Prescriptive analytics involves using historical data to predict events in the future while drawing helpful recommendations. This type of analytics outlines specific steps an individual or organization can take to achieve desired results or the best course of action.

Data Management 52

Data Management IBM Maintenance Healthcare IBM cost 52