Blogs

Blogs

Data Management

Blend, cleanse and prepare data for analytics, reporting, or data modernization efforts.

Artificial Intelligence | Data Management | Innovation
Matt Becker 0
Steps to building regulatory readiness for the next wave of clinical submissions

The regulatory submission process in life sciences is becoming less about assembling documents and more about proving trust. For years, submission readiness was largely treated as an end-stage operational milestone: finalize the analysis, validate the outputs and package everything for regulators. But that model is beginning to break down under

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English
Life Sciences
Data Management | Innovation | Internet of Things
Saurabh Mishra 0
Enterprise AI agents: Requirements for reliable data access

Many conversations about AI agents focus on models and frameworks. But when organizations attempt to deploy agents in real operational environments, a different challenge quickly emerges. How agents reliably and securely access enterprise data. Without reliable access to relevant data, AI agents struggle to support operational decisions. Whether diagnosing equipment

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English
Artificial Intelligence | Data Management | Innovation
Reyk Mikles 0
What a modern governance platform looks like – and how to choose the right one

Governance, risk and compliance (GRC) has evolved beyond a control mechanism or regulatory safeguard. In today’s environment, it forms the operational backbone of effective corporate management – enabling organizations to identify risks early, meet regulatory expectations reliably, and ensure that decisions and processes remain transparent and traceable. Yet many organizations still

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English
Banking | Government | Health Care
Artificial Intelligence | Data Management
Mark Lambrecht 0
Agentic AI in health care and life sciences: autonomy, accountability and the architecture of trust

With all the change that’s happened in the past decade, a few key things remain the same across health care and life sciences. Clinical trials remain the engine behind every new therapy, care delivery systems determine whether patients receive timely and effective treatment and health care payers must steward finite

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English
Health Care
Data Management | Innovation | Risk Management
Reyk Mikles 0
Governance in practice: Turning theory into day to day control

Governance, risk and compliance (GRC) frameworks are well established on paper. Most organizations have strategies, policies, risk registers and controls in place. Yet for many leaders, the reality looks quite different. Processes remain opaque. Responsibilities blur across functions. Regulatory changes trigger reactive workarounds rather than controlled execution. Audits consume excessive

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English
Analytics | Data Management
Jarno Lindqvist 0
From chaos to chorus: How to conduct open data architectures with precision

Data is growing faster than most organizations’ ability to manage it. At the same time, business leaders are under pressure to deliver insights quickly and cost‑effectively. Traditional, closed systems often make that harder: they lock data into proprietary formats, increase duplication and limit flexibility. That’s why open data architecture is

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English
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