3 Reasons Why AI and Big Data is needed in Business? | Big Data and B2B | AI and Data Analytics in B2B

3 Reasons Why AI and Big Data is needed in Business? | Big Data and B2B | AI and Data Analytics  in B2B

AI and BigData are compulsory in business. Today is the high time to implement AI in B2B. AI and machine learning algorithm process the data from BigData cloud to make decisions efficiently. Information is gathered from BigData, used as parameters to feed machine learning algorithm as input.

AI and BigData are interdependent to each other. Nowadays, AI uses BigData to make decisions and predictions. In B2B(Business to business), BigData plays an important role. BigData and AI reduce human efforts to make the decision. It is very difficult to use Business Analytics and taking the decision according to the result of the analytics and time taking too. So, we can introduce BigData and AI in our Business to improve business result and efficiency of our company. Machine learning is a magical tool, which only needs data as input. It automatically finds the pattern from the data given to the algorithm and gives the decision according to the pattern. Patterns are made from the decision taken in the past where situations are the parameter for taking the decisions.

So, we can improve our business by taking AI and Machine learning as a tool. But, we need a good input to get a great result from these tools. Here BigData comes into the picture. Big data provides us with an enormous amount of Data that we feed to these powerful tools to make the decision. The neural network works here to find the fine tuning of the parameters, which are extracted from the information provided by BigData.

AI and BigData in B2B

How can we improve our B2B experience using AI and BigData?

Lead Generation: Good lead is a gem for any business or any organization but you have to give a large amount of effort and time to find a good lead. You may publish some advertisement on online job sites or you may search an enormous profile to find the best match for the post. Then, you have to take interview of all the shortlisted candidates. But, when AI and BigData come into the picture, the whole concept changes. AI and machine learning algorithm will find out a perfect match for your company. AI will gather unstructured data from the BigData storage such as email, phone call, social post and profile on the internet and it will find some pattern from the gathered data, then it will provide the best match available with all the statistics like habit, daily life, efficiency, interest and skills.

How can we reduce our workload using AI and BigData?

All the IT professionals like us, know the meaning of redundant work. Right? We have to perform repetitive work and these type of work is important too. Sometimes we become depressed from these monotonous works and suffers mental-emotional illness so that we cannot focus on our own field, we cannot utilize our brain to innovate new things or pursue our passion. We used to work an extended hour or late night to meet our timeline. At the end of the day, the efficiency of the company decreases due to a depressed mentality of all the employees. Here, AI comes as an angel. You just need to put all the previous data to train the algorithm, then just provide the data to get the expected output. Computers are good at repetitive work, so it performs the repetitive work and trains itself from the feedback of each and every execution.

AI is needed to be implemented in all organizations; it will give lots of reasons to implement now otherwise you will be standing behind in the terms of improvement and revenue. 

How can we take decisions using AI?

Best use of AI in any kind of business is to make a future prediction. The ability to analyze and act on data is increasingly important to businesses. Each and every organization produces a huge amount of data on daily basis but it is very difficult to analyse all those data and bring out an information out of all the data.  Researchers from the University of Texas found that companies can generate big financial returns by making small improvements in data quality, usability, intelligence, remote accessibility and sales mobility. The 2010 study found that the average company could increase annual sales per employee by 14.4 percent if it increased the usability of its data by 10 percent. For the average Fortune 1000 company in the study, this amounted to a potential increase in productivity of $55,900.

“Data Analytics refers to qualitative and quantitative techniques and processes used to enhance productivity and business gain.”

Data are being utilised by AI for business solutions

There is no use of raw data or unprocessed data until or unless we make it processed. Processed data means information. Information produces parameters, which are used as an input to the AI and machine learning algorithm. This algorithm tunes its nodes according to the parameters and value of the parameters provides by the information. Now, AI is ready to provide future decisions based on these data with less than 5% error rate. Now, you have given parameter values as input and it will give a solution to achieve your goal.

Now we are in the “Analytics 4.0” era, the “rise of autonomous analytics,” written by Davenport and Harris.

                                                                                                                                                    Image courtesy: www.cisin.com