-
4 minutes
Building a Dashboard That Leadership Actually Used (Case Study)
Read More ->: Building a Dashboard That Leadership Actually Used (Case Study)A case study on a global derivatives dashboard. What started as a simple Tableau build ended up shaping future ETL automation, data scraping pipelines, and dashboards for years.
-
5 minutes
How to Get Hired as a Financial Data Analyst with AI (2025)
Read More ->: How to Get Hired as a Financial Data Analyst with AI (2025)AI isn’t taking financial data analysts jobs, it’s changing the definition of them. In modern finance, the analyst’s role is evolving from reporting the past to predicting the future. Those who can harness AI-driven insights, automate workflows, and communicate results clearly are redefining what “analysis” means in the age of intelligent automation. For financial data analysts and data scientists, this shift brings new questions: Which skills are still essential? Which tools are becoming obsolete? And how do you stand out in a market where AI can write code, generate dashboards, and even summarize 10-Ks? This guide unpacks what the data…
-
4 minutes
Top 5 Power BI Dashboard Tips to Improve Your Reports Today
Read More ->: Top 5 Power BI Dashboard Tips to Improve Your Reports TodayPower BI has helped democratize dashboards by giving anyone, from aspiring data analysts to business managers, the tools to explore, visualize, and share insights. Building a Power BI dashboard that looks good is easy, but building one that actually works takes intention. In our last article, we looked at why most Power BI dashboards fail and the five common mistakes behind them. This time, let’s fix them with five practical, easy-to-apply Power BI tips you can use today.
-
8 minutes
Dashboard Design Best Practices: From Charts to Clarity
Read More ->: Dashboard Design Best Practices: From Charts to ClarityOver the past few years, dashboards have become ubiquitous. Thanks to the “democratization of data visualization tools,” everyone is suddenly an analyst. With drag-and-drop interfaces and endless templates, it’s never been easier to pull data into a dashboard and share it with colleagues or executives. The problem? Most dashboards are bad. They don’t follow dashboard design best practices. You’ve probably seen them shared on LinkedIn: messy color schemes, overcrowded with charts, crammed into tiny panels, or spread across dozens of pages. They look neat, but they don’t communicate. At best, they confuse. At worst, they actively mislead.
-
17 minutes
Programmable Finance on DLT: Data-Centric Perspective
Read More ->: Programmable Finance on DLT: Data-Centric PerspectiveIn this weeks article we discuss how distributed ledgers reshape settlement data, risk metrics, and privacy controls in financial markets. The rise of programmable finance on DLT is reshaping how financial institutions think about settlement, data governance, privacy, and risk. Unlike earlier blockchain hype, today’s experiments focus on the data foundations of trust: ensuring interoperability across rails, clear definitions of finality, and privacy-preserving analytics at scale.
-
8 minutes
The Democratization of Data Visualization: Lessons from Plotly
Read More ->: The Democratization of Data Visualization: Lessons from PlotlyFor decades, data visualization was the guarded domain of BI specialists, statisticians, and data analysts. If an executive wanted a dashboard or a policymaker needed an analysis, they had to request it through a central analytics team and wait days or weeks for results. That world is gone. Today, thanks to platforms like Tableau, Power BI, and open-source frameworks such as Plotly Dash and Plotly Studio, almost anyone can spin up an interactive dashboard. This shift, known as the democratization of data visualization, promises faster insights, broader participation, and fewer bottlenecks from overworked data teams or gaps in expertise.
-
22 minutes
How to Create and Validate Synthetic Financial Data in Python
Read More ->: How to Create and Validate Synthetic Financial Data in PythonRecently Data Sense published an article discussing how synthetic financial data is reshaping risk management in financial services. We detailed how financial regulators have begun to experiment and publish guidelines for implementing and assessing synthetic data for analytical fidelity and privacy preservation. But how can this actually be achieved? Extending our previous research, we have provided a framework below for economists, supervisors and financial data scientists to implement and assess synthetic data use cases. The objective of this tutorial is to help economists, supervisors, and financial data scientists gain practical experience in generating, validating, and assessing synthetic financial data using…
-
10 minutes
Synthetic Data in Financial Services: Reshaping Risk
Read More ->: Synthetic Data in Financial Services: Reshaping RiskAs synthetic data in financial services gains momentum, evidence from the Financial Conduct Authority (FCA), the European Commission (EC), and central-bank forums shows it can help close cross-border visibility gaps in risk monitoring and systemic oversight When Lehman Brothers collapsed in September 2008, supervisors around the world struggled to see how risks were propagating through interconnected balance […]
-
20 minutes
Financial Data Automation ROI: A Data Professional’s Guide
Read More ->: Financial Data Automation ROI: A Data Professional’s GuideThe financial services sector is experiencing a data automation revolution, with 82% of CFOs increasing investments in digital technology in 2024, yet 49% of finance departments still operate with zero automation, relying on manual data entry and Excel spreadsheets (Solvexia, 2025). For data professionals, demonstrating financial data automation ROI has become critical as organizations seek […]
-
6 minutes
GraphRAG is The Next Evolution in Economic Data Analysis
Read More ->: GraphRAG is The Next Evolution in Economic Data AnalysisHow knowledge graphs are transforming economic analysis by connecting quantitative data with institutional insights The Challenge Every Economic Analyst Knows Too Well Economic analysis today presents a fundamental challenge: the data we need exists in two separate worlds that rarely speak to each other. On one side, we have rich quantitative datasets like the World […]
-
11 minutes
12 Amazing Dashboard Tools for 2025
Read More ->: 12 Amazing Dashboard Tools for 2025The data landscape in 2025 is more dynamic and demanding than ever before. The data landscape in 2025 is more dynamic and demanding than ever before. Businesses are drowning in data but starving for insights. Manual data wrangling, complex setups, and the perpetual need for specialized data teams often trap great ideas and stifle agility. […]
-
4 minutes
Uncover the Power of AI Agents in Data Analytics
Read More ->: Uncover the Power of AI Agents in Data AnalyticsArtificial Intelligence (AI) is rapidly transforming every industry, and data analytics is no exception. While traditional analytics tools have empowered businesses with insights, the next frontier lies in AI agents: autonomous or semi-autonomous systems capable of performing complex data tasks, from collection and cleaning to analysis and even recommendation, with minimal human intervention. At Data […]
-
13 minutes
Telling Amazing Stories with Data
Read More ->: Telling Amazing Stories with DataThe secrets of story telling There is nothing worse than a presenter who throws up a PowerPoint and begins to read off the screen. Despite how good the presenters data and analysis may be, the presentation comes off as dull and boring and leaves the audience with little recollection of the information. There’s an art […]
-
12 minutes
The Popular Trends in Data Visualization in 2025
Read More ->: The Popular Trends in Data Visualization in 2025In the rapidly evolving field of data visualization, staying ahead of trends can be difficult for professionals seeking to create impactful and insightful visual content. As we progress through 2024, several key trends are shaping the way we visualize and interpret data. Here we discuss the four most significant trends that are influencing data visualization today and will continue to do so in the coming years.
CATEGORY ARCHIVES













