How do we capture and leverage innovation as the engine for change?

This document discusses the absence of facts that can occur in businesses due to siloed, incomplete, or inaccurate data governance. It notes that while businesses have more data available than ever, more data does not necessarily lead to more insights or successful strategies. The document then examines some of the challenges that contribute to fact gaps, such as inefficient data landscapes, lack of data governance and quality, and unused data. It proposes that closing fact gaps requires a people and process solution involving data management, quality assurance, and communication between business leaders and data scientists.

Insurance Organizations Need Access to Good Data Before They Can Benefit from...

Captricity

The New Energy Consumer: What Promises Do Blockchain Technologies Offer Energ...

Wsta event 3 19-2015.v6

Kevin Petrie

1) The document discusses how financial services companies can better manage large amounts of data (big data) through automation and flexible platforms. 2) It recommends that companies derive their big data strategy from corporate strategy and educate workforces. It also stresses the importance of failing and iterating quickly. 3) The document promotes Attunity's data management solutions for automating tasks like data integration, replication, and movement between data warehouses and Hadoop in order to more efficiently analyze data and accelerate innovation.

CWIN17 san francisco-blockchain three ways to prevent it from failing in the ...

Capgemini

The document discusses three ways to prevent blockchain from failing in the enterprise. It first addresses challenges in the enterprise that can hinder blockchain's success, such as a lack of awareness of blockchain's impact and internal frictions. It then recommends conducting a targeted proof of concept on a practical use case to test business and technology aspects. Finally, it suggests getting an organization's "house in order" by intentionally breaking down silos, preparing for accelerated evolution, and embracing a cloud native development approach.

SVIA Insurance Disrupted Conference 2016 - The Disruptive Impact of Modern T...

Captricity

This document discusses how data and analytics can create or destroy shareholder value for companies through decision making. It finds that while most executives recognize the importance of data-driven decisions, only a third of organizations are highly data-driven. Highly data-driven companies are 3 times more likely to improve decision making. The technologies for advanced analytics like machine learning, IoT/sensors, simulation, and visualization are advancing rapidly but organizations must focus on developing the right operating model and skills to realize benefits. The operating model chosen can determine whether shareholder value is created or destroyed through analytics.

Bootstrap Big Data Webinar

Jane Truch

This document is a presentation on big data given by Martyn Crew, founder and CEO of Catch the Big Data Wave. The presentation defines big data, discusses why it is important to customers, outlines the big data ecosystem and options available, and who is making money from big data currently. The agenda includes defining the 3Vs of big data, examining big data's importance to customers, reviewing the big data ecosystem and options, identifying sectors making money from big data, and addressing that big data solutions can vary in scale and need.

Abn amro altares Marijne le Comte

IBM Innovation Center Silicon Valley

1) ABN AMRO conducted an investigation into data quality issues in 2015 which identified 700 issues clustered into 7 themes, with a focus on improving customer and reference data. 2) To address these issues, ABN AMRO developed a future state architecture detailing how to better manage reference and customer data through a unified approach. 3) Several challenges in resolving data quality issues quickly were identified, including the need to better share common data across business units, define consistent data meanings, and identify single sources of truth for critical data elements.

Infrastructure Matters

This document discusses how new trends in technology are changing business needs and placing new demands on IT infrastructure. Mobile, social, cloud, big data and analytics are driving more dynamic workloads and the need for more agile and efficient IT environments. This is requiring infrastructure that is scalable, flexible, reliable, secure and manageable. The document argues that composable infrastructure solutions enabled by cloud help meet these new demands, allowing infrastructure to be more real-time, agile, efficient and open. It provides examples of how IBM solutions for storage, servers, software defined infrastructure and cognitive systems address these infrastructure challenges.

Information Security Forum (ISF) Congress 2013

NIHR Clinical Research Network

The document discusses open data in clinical research and how it relates to big data. It notes that open data means data that can be analyzed and used by anyone through linkages and evidence-based applications. The document outlines key principles for open data, including clarity of use, data quality, and managing data reuse. It describes benefits like crowd-sourcing analysis, data linkage insights, and improved data quality. Finally, it summarizes that for clinical research, open data is a way to securely analyze and apply insights from big data.

Accenture Big Data Expo

This document discusses Accenture's approach to data modernization. It outlines key trends in data-driven organizations, including democratizing data, incorporating new data sources, focusing on advanced analytics, adopting big data and hybrid architectures, and changing skills requirements. The document then presents a high-level 9-step approach to agile analytics that engages stakeholders, identifies value opportunities, formulates hypotheses, understands data sources, defines models, prepares data, prototypes and iterates, pilots and executes projects, and delivers actionable insights. It also notes some common challenges organizations face in data transformation, such as unrealistic technology expectations, inadequate delivery approaches, skills gaps, and poor data governance. Finally, it poses questions to help organizations assess their readiness

Effective Solutions for Your Supply Chain Risks

Have you considered the supply chain risks associated with your business? Here we’ll identify the most common risks, the departments they affect, and their potential financial impact on your company. We’ll also address some solutions for preparation, prediction, and management that can have a huge impact on your business. Your supply chain shapes investment plans, production processes, manufacturing decisions, and more for the entire company. Using top-tier management tools ensures accuracy and provides you with a comprehensive view of your supply chain risks. Learn more about real supply chain impacts and innovative risk solutions below. http://halobi.com/2015/08/effective-solutions-for-your-supply-chain-risks

Asking the Right Questions of Your Data

DataWorks Summit

Executives are still waiting on our “Big Data Deep Insights”. Many of us are down the path of collecting, extracting, and analyzing our ever-growing data in Hadoop environments. We are building our data science expertise and expanding data governance. Yet still we are not getting what we are waiting for.This talk is about: 1. Getting to the right questions 2. Setting expectations with the executive team 3. The unintentional consequence of suddenly having lots of data 4. Framing the boundaries of our data science 5. Pragmatic data governance 6. Looking outside your data to 3rd party data

Top Five Trends That Are Redefining Banking in ASEAN

Best Practices In Predictive Analytics

Capgemini

Predictive analytics uses statistical techniques and business intelligence technologies to uncover relationships within large datasets to predict future behaviors or outcomes. While predictive analytics can provide benefits like reducing customer churn or improving marketing campaign response rates, it is not widely used due to complexity, underestimating value, high software costs, and reliance on good quality data. The document outlines best practices for predictive analytics including focusing on data management, expecting incremental improvements over time, measuring impact using business metrics, and gaining executive sponsorship for projects.

Knowledge Services: Mobilizing Scientific Knowledge to Serve Canadians

Albert Simard

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Information Management Strategy to power Big Data

Leo Barella

Modern Data Management

SAP Technology

Traditional data management approaches are inadequate to handle today's data growth and real-time business needs. Siloed technology stacks have become too complex, slow, and expensive. This is driving many enterprises to rethink their data strategies and build self-service platforms that can consolidate different data sources and provide faster, more flexible access to data. An end-to-end data architecture is needed to collapse silos, integrate data, and support real-time analytics and decision making across the business.

CV Toon D'Hollander

Toon D'Hollander

Toon D'Hollander is a data management consultant with 10 years of international experience. He specializes in data governance strategies and implementations to reduce costs and comply with regulations. He has experience developing data management strategies, assessing maturity, and driving data-focused roadmaps and business cases. He also has expertise implementing master data management, reference data, business glossaries, and data lineage.

General Data Protection Regulation (GDPR) Implications for Canadian Firms

Towards the Next Generation Financial Crimes Platform - How Data, Analytics, ...

Moving from passive to active data governance

Gary Allemann

How technology and innovative processes can make your legal team more efficient

Eversheds Sutherland

Technology Solutions for Manufacturing

Insight

In today’s globalized, competitive marketplace, being able to leverage technology to deliver faster turnaround times, meet lower pricing goals and provide customizable options can mean the difference between sustainability and irrelevancy. In this ebook, we’ll explore some of the leading solutions transforming the manufacturing industry: - Automation for cost savings - 3D printing for improved productivity - Smart data for quality assurance - Connectivity for safety and communication - Security solutions to protect it all Learn more: http://ms.spr.ly/6006Twegg

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