Knowledge sharing the 7 advantages

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The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.

Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.

Change management success for data governance

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As a data management professional you know that improving data governance is a top priority for many organisations. We know that data governance frameworks, processes and tools only enable benefits to the extent that our stakeholders adopt and use them effectively. As well as technical proficiency and good project management and delivery, data governance success also requires effective change management. Preparing for change, managing change, and sustaining change are critical steps on the journey to effective data governance. So how can data management professionals best use change management principles and techniques to contribute to the success of our data governance initiatives? This presentation was prepared to accompany a Data Management Association Australia webinar on change management success for data governance initiatives. Aims of the facilitated discussion in the webinar were to explore: How change management can enable the success of your data governance, reporting and analytics initiatives. Common people change related challenges that many data governance, reporting and analytics initiatives need to navigate. Change management techniques you can use to drive successful project delivery, change adoption and sustainable use of data governance, and reporting and analytics solutions. How to identify the top change management priority for your own current project, and the change management techniques that you can use to address it.

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Data Leakage is an important concern for the business organizations in this increasingly networked world these days. Unauthorized disclosure may have serious consequences for an organization in both long term and short term. Risks include losing clients and stakeholder confidence, tarnishing of brand image, landing in unwanted lawsuits, and overall losing goodwill and market share in the industry.

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everyone need to some storage and data.this big data is increase the data capacity and processing power. Big Data may well be the Next Big Thing in the IT world. • Big data burst upon the scene in the first decade of the 21st century. • The first organizations to embrace it were online and startup firms. Firms like Google, eBay, LinkedIn, and Facebook were built around big data from the beginning. • Like many new information technologies, big data can bring about dramatic cost reductions, substantial improvements in the time required to perform a computing task, or new product and service offerings.

Incorporating ERP metadata in your data models

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“Opening Pandora’s box” - Why bother data model for ERP systems? This presentation covers : a. Why should you bother with data modelling when you’ve got or are planning to get an ERP? i. For requirements gathering. ii. For Data migration / take on iii. Master Data alignment iv. Data lineage (particularly important with Data Lineage & SoX compliance issues) v. For reporting (Particularly Business Intelligence & Data Warehousing) vi. But most importantly, for integration of the ERP metadata into your overall Information Architecture. b. But don’t you get a data model with the ERP anyway? i. Errr not with all of them (e.g. SAP) – in fact non of them to our knowledge ii. What can be leveraged from the vendor? c. How can you incorporate SAP metadata into your overall model? i. What are the requirements? ii. How to get inside the black box iii. Is there any technology available? iv. What about DIY? d. So, what are the overall benefits of doing this: i. Ease of integration ii. Fitness for purpose iii. Reuse of data artefacts iv. No nasty data surprises v. Alignment with overall data strategy

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Your data has value to your organisation and to relevant data sharing partners. It has been expensively obtained. It represents a valuable asset on which a return must be generated. To achieve the value inherent in the data you need to be able to make it appropriately available to others, both within and outside the organisation. Organisations are frequently data rich and information poor, lacking the skills, experience and resources to convert raw data into value. These notes outline technology approaches to achieving compliance with data privacy regulations and legislation while providing access to data. There are different routes to making data accessible and shareable within and outside the organisation without compromising compliance with data protection legislation and regulations and removing the risk associated with allowing access to personal data: • Differential Privacy – source data is summarised and individual personal references are removed. The one-to-one correspondence between original and transformed data has been removed • Anonymisation – identifying data is destroyed and cannot be recovered so individual cannot be identified. There is still a one-to-one correspondence between original and transformed data • Pseudonymisation – identifying data is encrypted and recovery data/token is stored securely elsewhere. There is still a one-to-one correspondence between original and transformed data These technologies and approaches are not mutually exclusive – each is appropriate to differing data sharing and data access use cases The data privacy regulatory and legislative landscape is complex and getting even more complex so an approach to data access and sharing that embeds compliance as a matter of course is required. Appropriate technology appropriately implemented and operated is a means of managing and reducing risks of re-identification by making the time, skills, resources and money necessary to achieve this unrealistic. Technology is part of a risk management approach to data privacy. There is wider operational data sharing and data privacy framework that includes technology aspects, among other key areas. Using these technologies will embed such compliance by design into your data sharing and access facilities. This will allow you to realise value from your data successfully.

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This Loras College Business Analytics Symposium breakout session presentation by Kiran Garimella, Ph.D., president and founder of XBITALIGN, explored the analytics center of excellence (CoE). A business analytics program is more than the application of data science and Big Data technology to data. Success should be measured not only by the valuable insights the program delivers, but also by how well it is sustained and how much the ‘analytics mindset’ becomes part of the company’s DNA. The journey is not only from data to information, but also from information to knowledge, and from knowledge to intelligence. The foundation for making this happen is a well-structured Analytics Center of Excellence (CoE).

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Forget Big Data. It's All About Smart Data

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This proposes an initial smart data framework and structure to allow the nuggets of value contained in the deluge of largely irrelevant and useless data to be isolated and extracted. It enables your organisation to ask the questions to understand where it should be in terms of its data state and profile and what it should do to achieve the desired skills level across the competency areas of the framework. Every organisation operates within a data landscape with multiple sources of data relating to its activities that is acquired, transported, stored, processed, retained, analysed and managed. Interactions across the data landscape generate primary data. When you extend the range of possible interactions business processes outside the organisation you generate a lot more data. Smart data means being: • Smart in what data to collect, validate and transform • Smart in how data is stored, managed, operated and used • Smart in taking actions based on results of data analysis including organisation structures, roles, devolution and delegation of decision-making, processes and automation • Smart in being realistic, pragmatic and even skeptical about what can be achieved and knowing what value can be derived and how to maximise value obtained • Smart in defining an achievable, benefits-lead strategy integrated with the needs business and in its implementation • Smart in selecting the channels and interactions to include – smart data use cases Smart data competency areas comprise a complete set of required skills and abilities to design, implement and operate an appropriate smart data programme.

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Building a Data Strategy – Practical Steps for Aligning with Business Goals

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Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.

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Many experts say the rise of embedded and wearable computing will bring the next revolution in digital technology. They say the upsides are enhanced health, convenience, productivity, safety, and more useful information for people/organizations. At KMWorld Confererence, Lee Rainie shares the latest findings from Pew Research about the internet and puts it into organizational context with the expanding Internet of Things.

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A business is, in essence, a vast collection of knowledge and information. It's what's behind the creation of benchmark products and services, and it exists as a web of insights and ideas shared by staff. It's in your documentation—your manuals, guidelines, lists, databases, memos, and files. And it's also in the minds of your team members, as the expertise you need to capture to enhance your business. Knowledge is power, and when properly harnessed, it fuels a successful company. Technology has had a tremendous impact on knowledge management (KM), inspiring the development of robust software platforms to leverage KM strategies. Knowledge management software continues to evolve in response to new demands and challenges. Let's look at 15 emerging knowledge management trends that are changing the course of knowledge management software.

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