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In the fast-paced world of today, there is a constant urge for companies to grow, and this has led to stiff competition among them.
This is where Data comes in and now more than ever, data quality is the primary determinant of one staying above the competition.
With tons of raw data available and the many advances in technology, data segregation and analysis have become more accessible for marketers and growth hackers alike. However, decision makers do not have a high level of confidence in their systems with providing them conclusive information on operational data.
What can be the Solution?
Artificial Intelligence is what helps us to look into data connections and enables us to look into patterns rather than atomic level events. While AI still has a long way to go before it replaces human decision making, it can indeed work when coupled with human analytics.
Here is a look at how AI aids in making data intelligent:
With contextual learning, AI can identify comparisons even when combining vast amounts of data. This area is critical as it helps people in finding relations to input components faster. It further improves the data quality as comparisons enhance the accountability of data.
Contextual learning has been boosted by linguistic-based knowledge wherein the AI framework can understand and extract data in an improved manner. It is also able to scale down large volumes of data and make interpretations.
Combined with Deep learning, AI can be effectively used to build pattern recognition models. AI helps decision makers understand patterns which may not always be possible with human analysis.
When data is extracted from these models, it can be used for intelligent problem solving which might be the end goal. Additionally, with contextual learning comes contextual awareness with which devices will be able to recognize behavioral patterns and function accordingly. This means that contextual information will help each user have a unique experience.
AI can help remove the bias present in the work environment today. Fundamentally, AI can impact hiring, lending and even legal systems in removing human bias.
Human beings make decisions by looking at patters that they attain when they are trained and some are attained from their life experiences and living environment. This is again filtered through the individual thought processes and a decision is finally made.
So a huge part of human decision making is dependent on what they already know. Thus human beings end up making unconscious assumptions. This will evidently lead to bias when data is collected and interpreted. Even though AI is also dependent on data patterns, algorithms can be trained to filter irrelevancies’ and it can eventually provide unbiased results.
Any data that is amalgamated from various sources tend to be more comprehensive and evidence based. Combining data from different sources is difficult and time consuming in traditional processes. By developing mapping techniques between data resources and application repositories, AI can automate data aggregation processes.
AI can be very beneficial for sorting through vast amounts of data and combining the same ultimately making it fit for reuse. AI can discover, sort and store data. AI can objectively identify data that has been used/unused. This helps organizations remove vast amounts of obsolete data while keeping the ones that they really need.
It thus makes data more dynamic by interpreting relations and providing understandable correlations. If your company has constant data streams, then AI can combine them and provide real time insights. These insights are useful as they can provide information associated with performance and may help in identifying unexpected outcomes.
There is a lot of opportunity to use AI in all kinds of decision making. With AI, one can turn to data-based models and simulations. This is augmented intelligence in action and if the organization is handling large chunks of data and making crucial decisions based on data analytics, then AI can significantly speed up the process.
Our future is with AI at the helm of decision making and when decision-makers have dependable data analyses, recommendations and follow-ups through AI systems, they can make better choices for their business.
Critical mistakes happen when executives are forced to make decisions. The quality of the decisions significantly decreases when they are made across a short period. Algorithms never tire. Hence the outputs they put out are consistent as well as to the point.
While advances in artificial intelligence have captured our imagination and led to extensive reception of AI-infused assistants, the primary concern of skeptics is accountability because there is no way of finding out how AI came to a specific interpretation.
They would want technology to be transparent for them to approve of it entirely. This is where human-assisted AI can combine the raw processing capacity and interpretations of AI data with human understanding and decision making in order to make better decisions.
At present, it is contributing effectively to industries such as healthcare, automotive, financial services, logistics, communication and more. These sectors have directly benefitted from AI which provides them with better data to interpret. As it evolves, AI will enter into more industries helping managers take measurable, smarter and more intelligent decisions.
Lymbyc, being the world's first virtual analyst has proven its mettle in the industry . Be it the "Most innovative Data science Product" by Aegis or "the top 10 emerging Analytics startups in India to watch out for in 2018" by Analytics India Magazine, Lymbyc is making heads turns and making headlines