ElegantJ BI

JANUARY 3, 2019

These business users have adopted business intelligence and advanced analytical tools to gather and analyze data from varied data sources and use that analysis to identify the root cause of problems, identify opportunities, solve problems and share crucial data to support business decisions.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Data Modelling 130

ElegantJ BI

JANUARY 3, 2019

These business users have adopted business intelligence and advanced analytical tools to gather and analyze data from varied data sources and use that analysis to identify the root cause of problems, identify opportunities, solve problems and share crucial data to support business decisions.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Data Modelling 130

ElegantJ BI

JANUARY 3, 2019

These business users have adopted business intelligence and advanced analytical tools to gather and analyze data from varied data sources and use that analysis to identify the root cause of problems, identify opportunities, solve problems and share crucial data to support business decisions.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Data Modelling 130

Smart Data Collective

APRIL 14, 2021

Main features include the ability to access and operationalize data through the LookML library. It also allows you to create your data and creating consistent dataset definitions using LookML. Formerly known as Periscope, Sisense is a business intelligence tool ideal for cloud data teams.

Business Intelligence 332

Business Intelligence Business Intelligence Big Data Visualization 332

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.

Business Analysis 130

Business Analysis Business Analysis Backlog Management Documentation 130

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

Astera

NOVEMBER 13, 2023

They facilitate testing different scenarios such as data creation, retrieval, update, and deletion. API Documentation: Postman can automatically generate API documentation based on OpenAPI definitions, which can be shared with developers and stakeholders for a better understanding. Apiary Apiary.io

Documentation 52

Documentation Visualization Data Modelling Project Management 52

Astera

NOVEMBER 14, 2023

If you have had a discussion with a data engineer or architect on building an agile data warehouse design or maintaining a data warehouse architecture, you’d probably hear them say that it is a continuous process and doesn’t really have a definite end. And that, in essence, is pretty much the truth.

Data Warehouse 52

Data Warehouse Agile Data Modelling Data Quality 52

Capiro

AUGUST 20, 2021

What is a business data architecture? A business data architecture comprises definitions and models of an organisation’s concepts and data using the language of the business. Master your business data. It forms a picture of the business in terms of the data. Advantages of a business data architecture.

Data Architecture 52

Data Architecture UML Agile Data Modelling 52

Sisense

SEPTEMBER 3, 2020

This includes database modeling, metrics definition, dashboard design , and creating and publishing executive reports. ROI (return on investment) is also a key concern, as business analysts apply their data-related activities to finance, marketing, and risk management, for instance. See an example: Explore Dashboard.

Chief Data Officer 97

Chief Data Officer Finance Data Modelling Visualization 97

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

Bridging the Gap

OCTOBER 12, 2022

I’ll be sharing specific techniques for business process analysis , use cases , and data modeling , as well as success stories from ACBAs. Now, the first slide I want to bring, just to kind of revisit these actual definitions and make sure we’re clear. Okay, so third element of COTS requirements is data modeling.

Skillset 52

Skillset Business Analysis Business Analysis Data Modelling 52

Astera

FEBRUARY 27, 2023

The biggest advantage of having a data vault in place is its adaptability to change. If your source architecture is prone to changes, such as the addition or deletion of columns, new tables, or new/altered relationships, you should definitely implement a data vault. But fear not; there’s an easy way out!

Data Warehouse 40

Data Warehouse Data Modelling Visualization 40

Tableau

OCTOBER 8, 2021

With its LookML modeling language, Looker provides a unique, modern approach to define governed and reusable data models to build a trusted foundation for analytics.

Government 133

Government Digital Transformation Healthcare Retail 133

Capiro

AUGUST 2, 2023

More about the elements of a requirement Data The scenario can identify the data needed for the function. It is useful to have a common a data model and/or database schema with agreed definitions of all data. Process models and data models will incorporate business rules.

UML 52

UML Banking Project Management Process Modelling 52

Bridging the Gap

MAY 25, 2022

We definitely need to include that for sure. Definitely in the midst of that or a little bit before that Laura hit my radar. Michael: But you definitely pushed through. So I’m definitely proud of you for that. So yeah, definitely people struggle with that, but also, the final module. Stephanie: Thank you.

Business Analysis 52

Business Analysis Business Analysis Documentation Data Modelling 52

Bridging the Gap

MARCH 5, 2024

The Software-Level , or how the software system supports the business workflows, often completed through functional requirements models like use cases and wireframes. The definition of business analysis allows for many different approaches to the role.

Business Analysis 52

Business Analysis Business Analysis Project Management Portfolio Management 52

The BAWorld

SEPTEMBER 2, 2021

This is a classic example of structured data and can be efficiently managed through a database. Unstructured Data. Unstructured data has no definite structure or data model and is stored in its native format.

Big Data 52

Big Data Data Warehouse Data Visualization Visualization 52

Tableau

OCTOBER 8, 2021

With its LookML modeling language, Looker provides a unique, modern approach to define governed and reusable data models to build a trusted foundation for analytics.

Government 98

Government Digital Transformation Healthcare Retail 98

Insight Software

JANUARY 15, 2021

There are definite steps you can take to increase customer value, win loyalty, and improve your chances of retaining those customers for the long haul. The required investment to develop reports on Power BI and Azure Data Lakes is considerable, and there are substantial liabilities to consider before making a costly long-term commitment.

Data Warehouse 72

Data Warehouse Supply Chain Finance Data Visualization 72

Data Pine

SEPTEMBER 29, 2022

Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. But first, let’s define what data quality actually is. What is the definition of data quality? 2 – Data profiling. This is definitely not in line with reality.

Data Quality 96

Data Quality Monitoring Big Data Government 96

Sisense

AUGUST 4, 2019

First of all, the definition of database. As you know, this data is organized into rows, columns and tables, and it’s also indexed so that you can find what you need quickly and easily. This will make it easier to visualize the different issues as we come to them. Understanding a M2M Relationship and Its Consequences.

Visualization 75

Visualization User Experience Data Modelling Big Data 75

Whizlabs

JUNE 2, 2021

Before you can go ahead with the preparatory moves, you need to understand the basic definition of Microsoft Power Platform App Maker and its certification. Individuals must gain knowledge on: Data modeling basics. 4 Modules- Create a Model-Driven application in Power Apps. No cards needed to try the test!

User Experience 52

User Experience Government Process Analysis Data Modelling 52

Sisense

JULY 24, 2019

In this mode, the user avoids putting too much effort into the definition of a specific search, and instead, relies on a random exploration path with the assisted exploration of NLQ. For new vendors in the analytics market, one of the most obvious challenges is the absence of historical data.

Skillset 89

Skillset Big Data Data Modelling Data Analytics 89

MindsMapped

SEPTEMBER 10, 2020

Knowledge Areas Percentage Weight (%) Business Analysis Planning and Monitoring 14% Elicitation and Collaboration 12% Requirements Life Cycle Management 15% Strategy Analysis 15% Requirements Analysis and Design Definition 30% Solution Evaluation 14% IIBA CBAP® Exam Blueprint.

Requirements Life Cycle Management 53

Requirements Life Cycle Management Business Analysis Business Analysis Design Definition 53

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. You may be storing higher-definition images in your PIM, but your ecommerce website needs lower resolution images because they are smaller and load faster. Image configurations.

Innovation 52

Innovation Data Governance Customer Experience Customer Experience 52

Sisense

APRIL 10, 2020

All common and necessary data science tasks (data loading, data analysis, data exploration, data preprocessing, data featurization, data modeling, and predictive modeling) are available in both R programming and Python languages. Both languages are user-friendly and easy to implement.

Visualization 98

Visualization Artificial Intelligence Data Mining Logistics 98

Sisense

APRIL 24, 2019

Be sure the query has a definite and unique purpose. Make sure all involved parties are in the discussion of developing your query. When querying production databases, make sure the DBA team is included. Focusing on business outcomes. Taxing the production database for exploratory or duplicative reports is an unnecessary risk.

Data Warehouse 111

Data Warehouse Data Modelling 111

Bridging the Gap

NOVEMBER 16, 2022

Our core teachings are around process analysis, like in process analysis , use cases , data modeling , which goes to that glossary of terms that you were talking about, and how to manage a whole project or really an initiative. LAURA BRANDENBURG: Well, thank you so much for that. LAURA BRANDENBURG: Yeah. This is a relatively new book.

Business Architecture 52

Business Architecture Digital Transformation Portfolio Management Vision 52

Sisense

AUGUST 11, 2019

We could argue over which definition of BA and BI are most accurate until the cows come home, but the real problem here is that different people use them to mean wildly different things. Well, for one reason: at some point, you need to figure out which technologies, tools, and approaches you should invest in to get the insights you need.

Business Intelligence 75

Business Intelligence Business Intelligence Data Mining Predictive Analytics 75

MindsMapped

JANUARY 5, 2021

Requirements Analysis and Design Definition. This task describes a set of requirements or designs in detail using analytical techniques such as data modelling, user stories, use cases and scenarios, among others. By analysing elicitation results, requirements can be refined into requirements and designs.

Business Analysis 94

Business Analysis Business Analysis Skillset Solution Evaluation 94

Bridging the Gap

OCTOBER 26, 2023

Once you understand data mapping, you’ll be empowered to tackle data migration and system integration projects with confidence! For a little context, by the time that you are at this stage of the project, this is definitely not the first technique that you would be using most often.

Data Modelling 52

Data Modelling Vision Business Analysis Business Analysis 52

Marutitech

JANUARY 21, 2022

Identifying the correct data to process the underlying problem is essential to predict the suitable working model of your data science project. . Apart from reducing the data set, train your model to differentiate and classify your data. Product Management Tips for Data Science Project. 1.

Project Management 113

Project Management Data Mining Data Analytics Data Analytics 113

Timo Elliott

NOVEMBER 30, 2022

Gartner says that data is a liability – after all, it costs you money to collect, and it has risks, the very definition of a liability. To turn it into an asset, you actually have to do something with the data, to change something in the way you do business. And that’s what often goes wrong.

Innovation 246

Innovation Vision Data Warehouse Logistics 246

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

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