Juice Analytics

APRIL 1, 2021

Ask a better question Data requirements can quickly turn into a laundry list of unrelated metrics, dimensions, and half-baked analyses. There are many data products designed to give the users a broad palette to explore a variety of data. Here’s an article with the five differences between exploration and explanation.

Data Requirement 134

Data Requirement 134

Analysts Corner

APRIL 25, 2023

In the age of the internet, smartphones, and social media, the amount of data generated every day has reached unprecedented levels. This data is referred to as big data, and it is transforming the way businesses operate. What is big data? Velocity refers to the speed at which data is generated, analyzed, and processed.

Big Data 130

Big Data Retail Customer Experience Customer Experience 130

Modern Analyst

APRIL 30, 2022

This is the first of a series of articles intended to help business analysts deal with the information aspect of information systems during requirements elicitation. Requirements are commonly categorized as either functional or non-functional.

Documentation 80

Documentation Data Requirement 80

ElegantJ BI

SEPTEMBER 30, 2021

When a business enters the domain of data management, it is easy to get lost in a flurry of promises, brochures, demos and the promise of the future. In this article, we will present the factors and considerations involved in choosing the right data management solution for your business.

Data Management 130

Data Management Data Warehouse Government Data Governance 130

ElegantJ BI

SEPTEMBER 30, 2021

When a business enters the domain of data management, it is easy to get lost in a flurry of promises, brochures, demos and the promise of the future. In this article, we will present the factors and considerations involved in choosing the right data management solution for your business.

Data Management 130

Data Management Data Warehouse Government Data Governance 130

ElegantJ BI

SEPTEMBER 30, 2021

When a business enters the domain of data management, it is easy to get lost in a flurry of promises, brochures, demos and the promise of the future. In this article, we will present the factors and considerations involved in choosing the right data management solution for your business.

Data Management 130

Data Management Data Warehouse Government Data Governance 130

Dataversity

JULY 17, 2023

For data-driven organizations, this leads to successful marketing, improved operational efficiency, and easier management of compliance issues. However, unlocking the full potential of high-quality data requires effective Data Management practices.

Data Requirement 130

Data Requirement Data Management Data Quality Data Governance 130

Dataversity

JANUARY 25, 2023

Over the past few years, enterprise data architectures have evolved significantly to accommodate the changing data requirements of modern businesses. Data warehouses were first introduced in the […] The post Are Data Warehouses Still Relevant?

Data Warehouse 130

Data Warehouse Data Architecture Cloud Computing Data Requirement 130

Dataversity

DECEMBER 16, 2022

Unsupervised and self-supervised learning are making ML more accessible by lowering the training data requirements. 2022 was a big year for AI, and we’ve seen significant advancements in various areas – including natural language processing (NLP), machine learning (ML), and deep learning.

Data Requirement 130

Data Requirement Artificial Intelligence 130

Smart Data Collective

NOVEMBER 6, 2019

Big data and cannabis are two seemingly different concepts. CBD companies are relying more on big data than ever before. In June, Nicole Martin wrote a very detailed article for Forbes on the role of big data in operations management for the cannabis industry. Data helps to drive every industry now.

Big Data 132

Big Data Digital Data Requirement 132

Roman Pichler

JUNE 7, 2021

The grid encourages you to divide the stakeholders into four groups, as I explain in more detail in my article Getting Stakeholder Engagement Right. Use data instead to make the decision. If you lack the relevant empirical evidence, consider pausing the decision-making process and collecting the data required. .

Finance 29

Finance Data Requirement Planning 29

BA Coach

NOVEMBER 4, 2024

Rather than relying on abstract requirements, this principle encourages business analysts (BAs) to use real-world scenarios and examples to demonstrate how a solution will satisfy a need. In our next article, we will explore the fifth Agile principle, “Understand What is Doable.” Stay Tuned!

Agile 52

Agile Business Analysis Business Analysis Vision 52

Marutitech

APRIL 7, 2022

This article will deep dive to cover the introductory look at predictive modeling and its process. This is where data cleaning comes in. . Data cleaning involves removing redundant and duplicate data from our data sets, making them more usable and efficient. .

Predictive Analytics 98

Predictive Analytics Data Modelling Data Mining Data Requirement 98

Argon Digital

AUGUST 4, 2022

It’s also a powerful tool to discover requirements and plan elicitation. I’ll walk you through how I’d do that in this article. Business Data Diagram Fundamentals. Let’s start by reviewing the basic structure of a Business Data Diagram. But then, I wanted to add the canvass and its associated data.

Banking 52

Banking Documentation Visualization Data Modelling 52

Argon Digital

AUGUST 4, 2022

It’s also a powerful tool to discover requirements and plan elicitation. I’ll walk you through how I’d do that in this article. Business Data Diagram Fundamentals. Let’s start by reviewing the basic structure of a Business Data Diagram. But then, I wanted to add the canvass and its associated data.

Banking 52

Banking Documentation Visualization Data Modelling 52

Domo

DECEMBER 5, 2017

Real-time data requires agile execution Real-time data is only as helpful as your ability to execute on it quickly. Following the example of companies like Amazon and Freddy’s, data-driven success will be increasingly defined by how organizations turn real-time data into real-time decisions and actions.

Real-time Data 52

Real-time Data Agile User Experience Data Requirement 52

Analysts Corner

NOVEMBER 28, 2024

We must be more than just number crunchers; we need to be visionaries who understand how to leverage data effectively within our organizations. The growing importance of data requires leaders to be poised to tackle new challenges. AI tools are transforming how we gather and interpret data. The key is to stay informed.

Data Analytics 130

Data Analytics Data Analytics Innovation Skillset 130

GAVS Technology

NOVEMBER 5, 2024

Human Error: Mistakes such as accidental data sharing or configuration errors that unintentionally expose data, requiring corrective actions to mitigate impacts. Data Theft: Unauthorized acquisition of sensitive information through physical theft (e.g., stolen devices) or digital theft (hacking into systems).

Cybersecurity 52

Cybersecurity Healthcare Monitoring Data Security 52

The Data Administration Newsletter

OCTOBER 5, 2022

Governance for Acquired Data / Selecting Sources Our next column in the series explores challenges with governing acquired data, and then we’ll introduce a framework for managing acquired data— the data acquisition lifecycle.

Government 52

Government Data Requirement Data Quality Data Governance 52

Inflexion Analytics

APRIL 15, 2024

Document Summarization: When you need to extract key points from extensive reports or articles, LLMs are up to the task. Data Efficiency: LLMs require relatively small amounts of domain-specific data to fine-tune.

Artificial Intelligence 52

Artificial Intelligence Documentation Digital Innovation 52

Inflexion Analytics

APRIL 15, 2024

Document Summarization: When you need to extract key points from extensive reports or articles, LLMs are up to the task. Data Efficiency: LLMs require relatively small amounts of domain-specific data to fine-tune.

Artificial Intelligence 52

Artificial Intelligence Documentation Digital Innovation 52

Netmind

MARCH 9, 2021

Organizations need to develop their ability to obtain and use relevant data that provides information-generation, knowledge, and, ultimately, learning for better decision-making. In this article, rather than getting into types of metrics, indicators, or specific techniques, I want to focus on how organizations can develop this capability.

Data Governance 52

Data Governance Government Data Requirement Vision 52

Netmind

NOVEMBER 1, 2020

Organizations need to develop their ability to obtain and use relevant data that provides information-generation, knowledge, and, ultimately, learning for better decision-making. In this article, rather than getting into types of metrics, indicators, or specific techniques, I want to focus on how organizations can develop this capability.

Data Governance 52

Data Governance Government Data Requirement Vision 52

The BAWorld

SEPTEMBER 18, 2024

Data Integration Overview Data integration is actually all about combining information from multiple sources into a single and unified view for the users. This article explains what exactly data integration is and why it matters, along with detailed use cases and methods.

Data Warehouse 52

Data Warehouse Finance Data Architecture Banking 52

Roman Pichler

JUNE 7, 2021

Listen to this article: [link]. There are two reasons for this: First, you usually require people’s expertise to help you tackle complex issues, for instance, to understand technical risks or the impact on the ability to market and sell the product. Use data instead to make the decision.

Finance 62

Finance Data Requirement Planning 62

The BAWorld

OCTOBER 17, 2024

And the main important question- How do they even manage to transform this huge raw data into meaningful insights that drive various decisions? Worry not, In this article, we will answer the following questions: What is a data warehouse? What is the purpose of data warehouse? How does a data warehouse impact analytics?

Data Warehouse 40

Data Warehouse Data Analytics Data Analytics Data Mining 40

Data Pine

MAY 2, 2023

To work effectively, big data requires a large amount of high-quality information sources. Where is all of that data going to come from? The future is bright for logistics companies that are willing to take advantage of big data.

Supply Chain 110

Supply Chain Logistics Big Data Customer Experience 110

Ntara

MARCH 21, 2023

In this article, we’ll share the information you need to prepare for the sunset of Universal Analytics on July 1 this year. Here are some of the questions this article will answer for you: Why do I have to update to GA4? What’s different about GA4 vs Universal Analytics?

Data Warehouse 52

Data Warehouse Planning Data Requirement 52

MindsMapped

JULY 9, 2020

This article elaborates on Business Analyst and Project Manager-specific competencies and responsibilities, plus highlighting areas where they overlap. Business Analysts and Project Manager’s Roles and Competencies. Does the Individual have the Relevant Skillsets to take on a Hybrid Role?

Project Management 78

Project Management Skillset Requirements Life Cycle Management Business Analysis 78

Astera

MAY 25, 2023

In this article, we’ll discuss two of the most popular DBMSs: MySQL and SQL Server. We’ll explain how they work and explore the differences between them, so you can confidently choose the best option for your data-centric needs. Scalability : MySQL is known for its scalability and can handle large amounts of data efficiently.

Data Warehouse 52

Data Warehouse Data Requirement Finance Data Security 52

Astera

JANUARY 18, 2024

Fivetran is a low-code/no-code ELT (Extract, load and transform) solution that allows users to extract data from multiple sources and load it into the destination of their choice, such as a data warehouse. So, in this article, we will explore some of the best alternatives to Fivetran.

Data Warehouse 52

Data Warehouse Data Quality Data Management Government 52

Astera

JANUARY 2, 2024

Relying on this data to power business decisions is like setting sail without a map. This is why organizations have effective data management in place. But what exactly is data management? What Is Data Management?

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Insight Software

JANUARY 17, 2022

The BI solutions you evaluate should be compatible with your current data environment, while at the same time have enough flexibility to meet future demands as your data architecture evolves. Also look for a vendor that supports generic connectors and has flexibility through APIs or plug-ins.

Business Intelligence 52

Business Intelligence Business Intelligence User Experience Embedded Analytics 52

Astera

MARCH 20, 2024

This article covers everything about enterprise data management, including its definition, components, comparison with master data management, benefits, and best practices. What Is Enterprise Data Management (EDM)? Similarly, developing and executing a successful data strategy also needs experienced personnel.

Data Management 52

Data Management Master Data Management Government Data Warehouse 52

Marutitech

OCTOBER 8, 2021

For instance, you can efficiently classify a newspaper article or a book by its most frequently used words. Since tagging data requires consistency for accurate results, a good definition of the problem is a must. These methods are beneficial for long texts. But if the sentences are short, the results will not be so accurate.

Monitoring 98

Monitoring Documentation Logistics Customer Experience 98

Astera

JUNE 14, 2023

With the ability to extract key data from digitized or image-based invoices, these software solutions are helping businesses save time and money while increasing efficiency. In this article, we’ll talk about automated invoice scanning software, including how it works, its limitations, and best practices.

Documentation 40

Documentation Digital Banking Data Security 40

Astera

MAY 6, 2024

It utilizes artificial intelligence to analyze and understand textual data. Therefore, it can help businesses extract insights from text-based sources such as social media posts, customer reviews, articles, and more. Can handle large volumes of data.

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52