Smart Data Collective

APRIL 4, 2022

However, many companies are struggling to figure out how to use data visualization effectively. One of the ways to accomplish this is with presentation templates that can use data modeling. Taking Advantage of Data Visualization with Presentation Templates. Keep reading to learn more.

Data Visualization 299

Data Visualization Visualization Data Modelling Big Data 299

Astera

MARCH 20, 2023

As data warehousing technologies continue to grow in demand , creat ing effective data models has become increasingly important. However, creating an OLTP data model presents various challenges. Well, there’s a hard way of designing and maintaining data models and then there is the Astera’s way.

Data Modelling 52

Data Modelling Data Warehouse Visualization Business Intelligence 52

Astera

MARCH 20, 2023

As data warehousing technologies continue to grow in demand , creat ing effective data models has become increasingly important. However, creating an OLTP data model presents various challenges. Well, there’s a hard way of designing and maintaining data models and then there is the Astera’s way.

Data Modelling 52

Data Modelling Data Warehouse Visualization Business Intelligence 52

Analysts Corner

FEBRUARY 12, 2023

It is widely used as a reference and training tool for business analysts. AI : The BABOK Guide defines various tasks and concepts related to business analysis, including requirements elicitation and analysis, process and data modeling, and stakeholder communication and management. Some suggestions include: 1. ID (primary key).

Business Analysis 147

Business Analysis Business Analysis UML Artificial Intelligence 147

Capiro

APRIL 12, 2019

This video introduces the basics of data modelling. Data modelling is fundamental to creating a business level data architecture. The business view is of course highly simplified; we are trying to explain data modelling, not the business of insurance. Notes on the model. Introduction.

Data Modelling 40

Data Modelling UML Data Architecture Business Analysis 40

BI Insight

FEBRUARY 9, 2022

Incremental refresh, or in short, IR, refers to loading the data incrementally, which has been around in the world of ETL for data warehousing for a long time. Let us discuss incremental refresh (or incremental data loading) in a simple language to better understand how it works.

Real-time Data 144

Real-time Data Data Modelling 144

Analysts Corner

MAY 14, 2023

Understanding the unique characteristics of time series data is crucial for effective modeling: Trend: This is a long-term increase or decrease in the data. Seasonality: This refers to regular, predictable changes in a time series that occur over a specific period, such as daily, monthly, or yearly fluctuations.

Finance 130

Finance Data Modelling Data Analytics Data Analytics 130

Smart Data Collective

MAY 29, 2023

Understanding Bias in AI Translation Bias in AI translation refers to the distortion or favoritism present in the output results of machine translation systems. This bias can emerge due to multiple factors, such as the training data, algorithmic design, and human influence.

Artificial Intelligence 182

Artificial Intelligence Documentation Data Modelling Monitoring 182

BizAcuity

MARCH 31, 2022

With the massive influx of big data, several businesses use AI platforms to help save costs in a number of ways including automating certain procedures, speeding up key activities among others. Predictive Analytics: Predictive analytics is the most talked about topic of the decade in the field of data science. Hope the article helped.

Artificial Intelligence 130

Artificial Intelligence Data Analytics Data Analytics Predictive Analytics 130

Tableau

JULY 25, 2024

Spencer Czapiewski July 25, 2024 - 5:54pm Thomas Nhan Director, Product Management, Tableau Lari McEdward Technical Writer, Tableau Expand your data modeling and analysis with Multi-fact Relationships, available with Tableau 2024.2. You may have heard of Multi-fact Relationships informally referred to as “shared dimensions.”

Retail 74

Retail Data Modelling Visualization Finance 74

BizAcuity

APRIL 1, 2023

The Data Warehouse can scale up to 2048 nodes, thus offering data storage ability up to 94 petabytes. By paying attention to data temperature, Teradata can deliver higher query throughput and more consistent response times. Data compression includes both value-compression and algorithmic compression of data.

Data Warehouse 130

Data Warehouse Monitoring Planning Data Modelling 130

BizAcuity

SEPTEMBER 22, 2022

The Data Warehouse can scale up to 2048 nodes, thus offering data storage ability up to 94 petabytes. The Data Model is designed to be fault-tolerant and be scalable with redundant network connectivity to ensure reliability for critical use case. Teradata Storage Approach and Challenges.

Data Warehouse 130

Data Warehouse Monitoring Planning Data Modelling 130

BizAcuity

APRIL 1, 2023

This may include combining variables, creating new variables based on existing ones, and scaling the data. Model Selection: A good model selection is one of the most critical steps in predictive analytics. And keep refining and revisiting the algorithms and models for optimal efficiency.

Predictive Analytics 130

Predictive Analytics Monitoring Banking Documentation 130

Analysts Corner

OCTOBER 10, 2023

That results in the conversion layer requiring data mapping as a BA artifact. Let’s talk about mappings We already discussed the massive challenge of reinventing the legacy Data Models, so let’s assume you have already done it. A BA needs to combine and maintain the mapping throughout an entire project timeline.

Documentation 130

Documentation Data Modelling 130

BizAcuity

JANUARY 18, 2023

This may include combining variables, creating new variables based on existing ones, and scaling the data. Model Selection: A good model selection is one of the most critical steps in predictive analytics. And keep refining and revisiting the algorithms and models for optimal efficiency. REFERENCES. [1]

Predictive Analytics 130

Predictive Analytics Monitoring Banking Documentation 130

Sisense

AUGUST 4, 2019

You can easily test if a relationship is Many-to-Many by checking the data modeling of the relationship and determining the exact number of unique and duplicate values on each side of the relationship. Picture a database that’s used by a university application to keep track of student data.

Visualization 75

Visualization User Experience Data Modelling Big Data 75

The BAWorld

NOVEMBER 20, 2024

Responsibilities: Creating basic reports and dashboards, connecting to data sources, and assisting in data modeling. Reference: AmbitionBox Mid-Level (3–5 Years): Salary Range: ₹6 Lakhs to ₹9.4 Reference: AmbitionBox Senior-Level (6+ Years): Salary Range: ₹10 Lakhs to ₹14 Lakhs per annum. Lakhs per annum.

Supply Chain 52

Supply Chain Pharmaceutical Healthcare Real-time Data 52

Business Analysis Knowledge Share

SEPTEMBER 17, 2023

By following these steps and using the mind map as a reference, you can design ERDs that effectively represent and simplify complex systems.

Business Analysis 69

Business Analysis Business Analysis Data Modelling Visualization 69

Sisense

AUGUST 28, 2019

Simply put, the term cloud-agnostic refers to the ability to move applications or parts of applications from one cloud platform to another. What does it mean for your data? But what does cloud-agnostic have to do with your chosen BI platform? Look for a Cloud-Agnostic Product Roadmap.

Cloud Computing 73

Cloud Computing Data Architecture Data Modelling Documentation 73

Ntara

OCTOBER 4, 2023

Most PIM software applications include basic DAM capabilities , providing a reference for accessing or publishing a product’s images and videos. However, as you start to rely more on digital assets to complement your product data, you may require additional capabilities and governance.

Government 96

Government Digital Data Modelling Data Management 96

Astera

JANUARY 11, 2023

The primary purpose of your data warehouse is to serve as a centralized repository for historical data that can be quickly queried for BI reporting and analysis. Data modeling — which defines the database schema — is the heart of your data warehouse . Learn more about designing Dimensional Data Models here. .

Data Warehouse 52

Data Warehouse Data Modelling 52

Sisense

JULY 3, 2019

Augmented Insights is how we refer to the area of our AI research that is dedicated to providing business users with a guided journey and deeper insights from their data. Recommended modeling when adding new disparate data Data deduplication and cleansing for those times when data isn’t perfect – and by that I mean always.

Innovation 74

Innovation Data Modelling Visualization Artificial Intelligence 74

Astera

JANUARY 11, 2023

The primary purpose of your data warehouse is to serve as a centralized repository for historical data that can be quickly queried for BI reporting and analysis. Data modeling — which defines the database schema — is the heart of your data warehouse . Learn more about designing Dimensional Data Models here. .

Data Warehouse 52

Data Warehouse Data Modelling 52

Tableau

SEPTEMBER 11, 2024

And with Tableau’s centralized permissions and data models, the app streamlines your data access and management by eliminating the need to replicate permission requests. Please refer to our detailed GitHub documentation for step-by-step guidance on setting up the app for Tableau Server. September 23, 2024

Documentation 69

Documentation Data Modelling Monitoring Product Management 69

GAVS Technology

JANUARY 7, 2021

While the importance of HIE is clearly visible, now the important question is how hospitals can collaborate to form an HIE and how the HIE will consolidate data from disparate patient information sources. This brings us to the important discussion of HIE data models. HIE Data Models. The two models are.

Healthcare 52

Healthcare Data Modelling Data Mining Government 52

Sisense

JULY 24, 2019

Without historical data, facilitating longer NLQ journeys in exploration mode will be somewhat limited at first. Imagine a marine freight company using Captain Cook slang to refer to distances (fathom), weights (draft), and types of goods (treasures) being shipped across oceans.

Skillset 89

Skillset Big Data Data Modelling Data Analytics 89

Marutitech

DECEMBER 17, 2021

You must be wondering what the different predictive models are? What is predictive data modeling? This blog will help you answer these questions and understand the predictive analytics models and algorithms in detail. What is Predictive Data Modeling? Applying the learning to different cases.

Predictive Analytics 140

Predictive Analytics Data Mining Finance Data Analytics 140

Bridging the Gap

MARCH 9, 2023

And they’ll use a variety of data modeling techniques to define how information is stored and flows through various systems. A business analyst in this type of role will use techniques such as business process analysis to understand the business workflow and the problem to be solved. What does that look like?

Skillset 98

Skillset Business Analysis Business Analysis Project Management 98

Marutitech

MARCH 10, 2022

Over or underfitting the predictive analytics solution is a common mistake that any data scientist makes while developing their model. Overfitting your data refers to creating a complicated data model that fits your limited set of data.

Predictive Analytics 130

Predictive Analytics IBM Maintenance E-Commerce IBM Support 130

Domo

AUGUST 4, 2023

All shortlisted vendors were determined through Constellation’s client inquiries, partner conversations, customer references, vendor selection projects, market share and internal research. The Constellation ShortList helps organizations narrow their search for the technologies they need to meet their digital transformation goals.

Embedded Analytics 52

Embedded Analytics Business Intelligence Business Intelligence Digital Transformation 52

Astera

DECEMBER 29, 2023

In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way. Free Download What is a Data Warehouse? Data is organized into two types of tables in a dimensional model: fact tables and dimension tables.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way. Free Download What is a Data Warehouse? Data is organized into two types of tables in a dimensional model: fact tables and dimension tables.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Sisense

JULY 6, 2020

First off, this involves defining workflows for every business process within the enterprise: the what, how, why, who, when, and where aspects of data. These regulations, ultimately, ensure key business values: data consistency, quality, and trustworthiness.

Data Management 98

Data Management Data Architecture Data Governance Government 98

Watermark Learning

OCTOBER 3, 2023

The International Institute of Business Analysis (IIBA®) created and maintains the BABOK Guide v3 , an indispensable reference for any business analyst. Data Modeling-Describes the data important to the business.

Process Modelling 86

Process Modelling Business Analysis Business Analysis Visualization 86

The Data Administration Newsletter

FEBRUARY 21, 2024

Explainable AI refers to ways of ensuring that the results and outputs of artificial intelligence (AI) can be understood by humans. It contrasts with the concept of the “black box” AI, which produces answers with no explanation or understanding of how it arrived at them.

Artificial Intelligence 52

Artificial Intelligence Data Modelling Data Governance Data Visualization 52

Capiro

AUGUST 20, 2021

A homonym refers to the use of the same term for different things; homonyms can also result in confusion and should be identified. Row 2: Conceptual – The conceptual row refers to models of the organisation’s concepts. Concepts might also be considered as ‘data classes’. Conceptual view of data. UML class diagrams.

Data Architecture 52

Data Architecture UML Agile Data Modelling 52

Astera

APRIL 23, 2024

However, certain metrics are commonly adopted across many industries for their fundamental importance in assessing data health. Here are some frequently used data quality metrics examples: Completeness Ratio It refers to the extent to which a data set contains all the required or expected data elements.

Data Quality 52

Data Quality Monitoring Data Modelling Data Warehouse 52