Making Advanced Analytics Work for You
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Advanced analytics uses sophisticated techniques beyond traditional business intelligence to discover deeper insights from data. It includes techniques like machine learning, data mining, and neural networks. While many major companies invest in analytics, some hesitate due to a lack of structured data or past failures. The document provides suggestions for effective advanced analytics, including choosing the right data sources, building models to optimize business outcomes, and embedding analytics in tools to generate maximum profit. However, companies must set boundaries on data use and consider ethics to avoid illegal or reputation-damaging practices.
Making Advanced Analytics Work for You
- 1. Making Advanced Analytics Work for You
- 2. Advanced Analytics is the autonomous or semi- autonomous examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations. Advanced Analytics
- 3. Advanced Analytic Techniques include: • Data/Text mining • Machine Learning • Pattern Matching • Forecasting • Visualization • Semantic Analysis Advanced Analytics
- 4. • Sentiment Analysis • Network and Cluster Analysis • Multivariate Statistics • Graph Analysis • Simulation • Complex Event Processing • Neural Networks Advanced Analytics
- 5. •Google and Amazon have turned into experts in eclipsing competitors with powerful new business models that derive from an ability to exploit data. The Risk of Advanced Analytics
- 6. • Despite many major companies investing in Analytics, there are companies that still hesitate to jump in the bandwagon. • They are either not prepared with the requirements of analytics such as structured and organized data or have suffered losses previously due to unsuitable data warehousing programs. The Risk of Advanced Analytics
- 7. The article makes the following suggestions to make Advanced Analytics work: • Choosing the Right Data: Searching for new sources of data such as social media or previously ignored data such as customer complaints and suggestions is a great way to start. The right IT support will help in cleaning up and structuring the data. Suggestions to make Advanced Analytics work
- 8. • Build models that predict and optimize business outcomes: The most effective approach to build a model originates with identifying the business opportunity and determining how the model improve performance. The company must develop the least complicated model to improve performance by studying volumes of data by putting basic requirements in mind. Suggestions to make Advanced Analytics work
- 9. • Transform the companies capabilities: Developing useful business-relevant analytics which are in sync with the company’s day-to-day processes and decision-making norms by embedding analytics into simple tools for the managers to understand is a way to generate maximum profit. The managers need to jump into the process in order to turn literate in data and analytics. Suggestions to make Advanced Analytics work
- 10. Insight • Analytics despite it’s huge benefits, can have some loop holes, especially in execution of ethics. • The companies need to set boundaries on what data to mine and analyse and what to abstain from. • There are several instances in which companies have become fixated on gathering customer information and use it unethical or illegal purposes.
- 11. Insight For E.g., some banks can harvest their customers’ checking account data and using advanced analytics to identify other products that the bank could cross-sell to them. While this might not be illegal, these actions hurt the reputation of banks and ultimately their business and profit.
- 12. Insight • Analysis, while can give great basis and guidance for decision making, can raise ethical questions about gathered customer data. For e.g., For a website or app, the customer has been asked consent for access for certain data, he refuses, the website or app can still record his aggregate behaviour and share, causing a breach of privacy.
- 13. Managerial Relevance • Advanced Analytics is growing not only first world nation MNCs but also in Indian companies. • An Indian manager has to jump into the bandwagon of Advanced Analytics in order to be able to make more informed decisions. • Without the guidance of the manager, the team of analysts can never make the required progress in developing capabilities in Big Data.