Monday, January 10, 2022


Information management systems play a fundamental role in deploying and continuously opening new information from the dynamic business environment, circulating information within the ecosystem seamlessly and responding to changes continuously.

 Information brings about business ideas; business ideas generate lots of information. In the digital era, information potential directly impacts the potentiality of the company. 

Information is the gold mine of business, the quality of intelligence depends greatly on the quality of information and the effectiveness of information management.

Information accuracy: Data can be accurate, consistent, timely, but data can also be shared among many different business groups. From a science and engineering perspective, there is a change of emphasis, especially because of the Variety dimension of data such as velocity, variety, or value. Classification = Relevance. You might have very clean data on your customer profiles, but necessarily that data is incomplete or irrelevant. The accuracy and compromise will continue to coexist across the span of information management. Data quality doesn't mean you pursue the perfect data, but the good enough data being transformed into useful information to achieve its value.

By “quality data,” it means clean, organized, actionable data from which to extract relevant information and insight. Blending data from multiple sources has always been challenging, and in the information-exponential world, there is quality data, but there’s no “perfect” data. If you want high-quality information, it has to be standardized and consistent. The better the classification and structure of your data, the better your search and analytical capabilities will be. Real information systems are business-oriented to integrate different pieces of components, with how people leverage quality information for accomplishing business goals and objectives, and unleashing organizational potential.

Information interpretation and presentation:
Data is critical. But it's just a first step, the data is a very important base, but the interpretation of those data is of equal importance. Just like the same story can be told with different points of view by different readers. How information is interpreted based on the perception, knowledge and communication ability of the interpreters. The conversation will move beyond dashboards, scorecards, data visualization. It will be about merging big data and traditional sources of data into a single interactive experience for the business user so they will be able to view and test different outcomes to "their story."

Information visualization will change how you think about the world. Right now there is a significant knowledge gap between having the data, interpreting it, and finally being about to visualize it. Information visualization can be big enough to show executives the big picture but needs to be nimble enough to stay focused. Get from 'big picture' initiatives down to how individual efforts contribute to corporate goals either strategically or tactically. It’s important to improve information reusability. The potential value of information depends on how the information will be used again in the future for either running a business or managing innovation in structural ways.

Information governance:
Planning, staffing, undertaking and moderating are where data governance is being applied. More attention needs to be placed on the conditions that allow information to flow and generate value rather than try to manage or control information. Information governance doesn't always directly deal with information classification or taxonomy or categorization issues in most data deployments. It is most often a structure for what you are going to do, who is going to do it /how it is going to be done /and how it is going to be repeated, make sure you have architectures, standards, stewardship, compliance and all the other stuff covered.

Data Governance should be seen as a good habit, not a software package or an old solution. The end result is their "big data'' will be viewed as accurate and trustworthy. proper data governance is not a one time exercise but a constant review. Successful companies with great data governance have set up governance committees that include representatives from various parts of the business and agree on how the data will look, be deployed to create value. Big Data does not need a big governance, but it takes agile governance practice to orchestrate an organization's information strategy, to ensure the big value can be achieved from the abundance of data and information flow.

Information is the gold mine all forward-thinking organizations dig through to capture business foresight and customer insight. Information management systems play a fundamental role in deploying and continuously opening new information from the dynamic business environment, circulating information within the ecosystem seamlessly and responding to changes continuously.


thanks for the helpful information

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