Systems | Development | Analytics | API | Testing

Organizations currently face a fragmented ecosystem of data sources, collection methods, and reporting requirements. Many rely on manual processes and disconnected systems, leading to inefficiencies and increased risk of errors—approximately 70% of organizations struggle with data consistency and validation. The financial sector has emerged as a primary driver of ESG data management evolution, with investment decisions increasingly tied to sustainability performance.

Managing ESG data is complex but essential. Gartner’s Market Guide for ESG Reporting and Management Software states, "Without integrated ESG reporting, companies risk compliance breaches and reputational harm." This guide provides a roadmap to tackle ESG challenges and build a robust reporting strategy.

The European Union is transforming the landscape of ESG reporting with the Corporate Sustainability Reporting Directive (CSRD). This groundbreaking legislation, approved in November 2022, sets new standards for transparency and accountability in sustainability reporting.

Keboola, in cooperation with Capgemini and Snowflake, is releasing “AI Data Management For Dummies," a book written to be an easy introduction to the world of discriminative and generative AI.

Keboola, the self-service data management platform, develops a comprehensive platform that simplifies Environmental, Social and Governance (ESG) data management. It automates data collection, monitors key performance indicators (KPIs), and provides real-time insights across all client entities. By replacing manual processes, it ensures precision, uniformity, and adherence to ever-changing regulations.

A big part of data teams’ responsibilities is dealing with the unpredictable. Data pipelines don’t always run without incident: you need to rerun processes and fix data processing issues—in other words, put out data fires—to keep stakeholders happy. For every significant roadblock, additional time and effort is given over to investigation and post-mortem reports to make sure the incident doesn’t reoccur. But naturally, they keep happening.

‍ In our previous article, The Key to Unlocking QSR Growth, we discussed the guiding principles that lay a strong foundation for success in the Quick Service Restaurant (QSR) industry. We highlighted the importance of data analytics for improved decision-making, automation, and scalable growth.

Authors: Martin Fiser, Field CTO at Keboola, and Martin Lepka, Industry Solutions at Keboola The Quick Service Restaurant (QSR) industry sits on a goldmine of data, yet many brands are only scratching the surface with their analytics. Locked within siloed Point-of-Sale (POS) systems across individual franchisees, this data remains underutilized rather than being put to work.

This year's Gartner Hype Cycle for Data Management report mentions self-service data management. It’s a game-changer that gives business users the power to work with data without constantly relying on IT, boosting data quality and making data available for analytics and decision-making. But what is it, really? How do you achieve self-service? Let’s take a closer look.

Historically, finance teams largely operated in the background, focusing on record-keeping, compliance, and ensuring that financial operations ran smoothly. Their primary responsibilities revolved around managing costs, balancing the books, and maintaining operational efficiency. In recent years, that has changed.