Data is of critical importance to any company, irrespective of their size. With ever increasing volumes of data available, companies are deploying business intelligence (BI) solutions that will enable them to make informed decisions driven by data. To be successful in a highly competitive world, companies need to not only prioritize implementing a modern BI approach, but also educate their workforce to be analytically savvy. For organizations to retain their competitive edge, organizations need to recognize the business roles, technologies and strategies that will enable them to improve their approach to BI. Utreee is one of the companies that specializes in creating and implementing Business Intelligence solutions the US, Puerto Rico and in the Dominican Republic with great success for local companies.

AI and machine learning

Many organizations are still unsure about what artificial intelligence (AI) can do for their business. While technology is rapidly improving, machine learning (ML) is fast becoming indispensable to analysts, providing help and improving efficiency. An analyst can have more time available to think about how their analysis will impact on the business and plan for the next steps by automating simple, labor-intensive tasks. This will also help analysts stay on top of their data flow. Without having to stop to analyze their numbers, analysts can drill deeper and ask the next questions. Although the potential of ML to help analysts can’t be denied, it’s crucial to understand that it should only be implemented when the outcomes are clearly defined. Although some may be concerned by being replaced, ML will in fact assist in making analysts more accurate and have more impact on the business.

Utreee implements Business Intelligence solutions in the US, Puerto Rico, and Dominican Republic. We are just a click away .

NLP (Natural Language Processing)

It is predicted that 50% of analytical queries will be generated via voice, natural language processing (NLP), or search by 2020. NLP will enable people to ask more subtle questions of data and get specific answers that could lead to improved insights and decisions. 

Engineers and developers will also make great strides in exploring how people are using NLP by determining how questions are asked. Big analytic gains will be made by resolving this ambiguity and understanding how NLP can augment diverse workflows. Opportunity are available not by using NLP in every situation, but by implementing it in selected workflows.

Crowdsourcing data governance

BI has been disrupted by self-service analytics, and the same is happening to governance. As the capabilities of self-service analytics grows, valuable new information and perspectives lead to innovative new ways of implementing governance. The wisdom of the crowd in governance is used both for getting the right data to the right person and for preventing the wrong person from accessing data. 

The modern governance model will use analytics strategies and BI where data engineers and IT departments curate and prepare trusted data sources. This will enable end users to use self-service to explore trusted, secure data.

Multi-cloud

An estimated 70% of enterprises will use a multi-cloud strategy by 2019. As companies become increasingly cautious about being locked into a single legacy solution, implementing and evaluating multi-cloud environments can reveal who provides the best support and performance for specific situations. Although this approach is flexible, it does increase costs by dividing workloads between providers and expecting internal developers to learn multiple platforms. With adoption of multi-cloud increasing, companies need to evaluate their strategy by measuring internal usage, adoption, implementation costs and workload demands for different platforms.

Chief Data Officers

Analytics and data are fast becoming crucial to every company. This could easily result in a gap being formed between CIOs and the business while battling governance and security versus speed to insight. The C-Suite is also being held more accountable for creating an analytics culture. This has led to the rise of Chief Analytics Officers (CAO) or Chief Data Officers (CDO). These roles communicate the value of analytics at all levels, overcome cultural barriers and lead business process change. The role of the CAO/CDO is focused on outcomes and they stimulate proactive C-level conversations to assist in developing analytics strategies from the outset.

The location of things

The location of things is a subset of IoT and it includes all devices that are used to sense and communicate geographic positions. Having access to this data enables users to take it into account when they assess usage and activity patterns. This technology is also used to track people and assets, and can provide more personalized experiences by interacting with mobile devices like badges and smart watches. 

In relation to data analysis, location-based information can be seen as an input against result outputs. Analysts can incorporate this information if the data is available to understand what is happening, where it is happening, and what they should expect to happen.

Conclusion

Every company has data available, but how they use this data will ultimately determine the value derived from it. Although the BI techniques discussed in this article are currently the major trends and will help organizations increase their competitive edge, there are many more that can assist organizations in reaching their full potential. It does not matter were you are, the US, Dominica Republic, Puerto Rico or any where, Data is critical to your company and Business intelligence can give you that technological edge you need to make your data count. At Utreee we specialized in creating BI solution that works just for you.

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