Initiateadvancedanalytics

In the human context, information drives awareness and triggers confirmation, validation, verification.

Compared to traditional organizations operated a couple of decades ago, today’s companies are inundated with heavy information flow with increasing volume, velocity, variety and diverse context, some structural, some un-structural; some current, some outdated. 

Information based analysis helps businesses uncover patterns, capture customer insight, or business foresight, make more effective decisions and lead transformative changes.

Allow businesses to interpret their past to better plan their future: The exponential growth of information is part of the business new normal, it brings both opportunities and risks for businesses’ survival and thriving. The information-analytics is the ability to access the right data at the right time and the right location to make data-based, on-time decisions; context-based suggestions and recommendations. Advanced analytics is a great space to come up with new business for any kind of customer, demonstrating which parts of their product and customer experience could be impacted as well as how to improve it.

There are a variety of analytics. They are used for different purposes, provide different results, and answer different questions. Information based hindsight enables people to understand what has happened and why, the information based predictive foresight is to predict the likelihood of a specific outcome happening, and goes further, take prescriptive analysis to act smartly for achieving high ended business results. The maturity of the business analytics methods, tools and competencies is based on how effectively you can explore quality data, ask the effective question, optimize the end-to-end business process, build the practical analytics model, and measure the results objectively.

Improvement of data quality, getting higher data quality is half way of successful analytics: Data quality directly impacts the quality of analytics. By “quality data,” it means clean, organized, actionable data from which to extract relevant information and insight. The quality data characteristics include such as accuracy, consistency, reliability, etc. In order to improve data quality, it’s critical to check data management effectiveness: Do you have reports from different sources that don't match? Do you have to combine this data somehow to get meaningful reports? Do you have robust business processes that make data better, more reliable or accurate than the others?

Data quality does not end with managing the incorrect entry of information, but the logic of data has to be taken into account too. Follow the old wisdom: "Quality has to be designed in, not inspected out.” Identification of data quality issues input points where the biggest problems are and focus on real problems, not on symptoms based on subjective feelings. You can walk through all the various dimensions of data quality; business context is a very important perspective. Data can be accurate, consistent, timely, but data can also be shared among many different business groups, it can be transformed, aggregated, derived for various business needs and ensure people at the different layers of hierarchy can make effective decisions consistently.

Whether to run real time data analytics or not depends on the need and purpose: Real-time data is often used for navigation or tracking. There is no delay in the timeliness of the information provided. Real data analytics provides fast data exploration, collects and analyzes operational data in real time, develops query and analysis capabilities; enable users to share and collaborate on information almost at the real time. The true power of advanced analytics comes when you integrate the data-based insights into business processes by applying the model in real-time to predict the likelihood of emerging events and take logical actions.

The pace of change is increasing, along with frequent disruptions. The insights obtained from data mining and real time analytics needs to be converted into an actionable plan and results validated in terms of business outcomes. To deliver value from analytics, look at historical data to analyze patterns and relationships in order to predict the future. Organizations must turn information into knowledge, insight, and wisdom, making the right decisions at the right time to solve problems timely.

The tricky bit with information is that, depending on the level of granularity and aggregation, you can use it for multiple purposes. In the human context, information drives awareness and triggers confirmation, validation, verification; quality information is one of the most important assets to shape a highly intelligent business. Information savvy leaders and professionals are information agents who can convert quality information to fresh knowledge and unique insight to implement strategies, fine-tune business models, and drive transformative changes.

Posted in: Big Data,Business Intelligence