Data The New Oil
In Business Data plays a critical role in three core areas.
• Improving Decision making
• Improving Operations
• Monetization of Data
Data enables companies to collect better market and customer intelligence. With the ever-increasing amount of data available, companies are gaining much better insights into what customers want, what they use, how they purchase goods and what they think of those goods and services. This information can be used to better decisions across all areas of the business, from product and service design to sales, marketing and aftercare.
Data Helps companies gain efficiencies and improve their operations. From tracking machine performance to optimizing delivery routes to even recruiting the very best talent. It can improve internal efficiency and operations for almost any type of business and in many different departments.
Data provides the opportunity for companies to build big data into their product offering - thereby monetizing the data itself. For Example, by placing sensors to agriculture machines on how the equipment is being used and diagnose breakdowns. These sensors also work for the farmers by offering access to data about when to plant, where the best patterns for ploughing and reaping. It is becoming an entirely new revenue stream for what was seen as quite a traditional company.
Problems With Implementing Data Analytics
Enterprises can derive substantial benefits from big data analysis. Nonetheless, there are a number of challenges to overcome too.
On the whole, Big data appears to be a topic that brings many benefits, but many problems as well. Only six percent of all respondents said that they see no issues connected with using big data technologies. Below are the challenges:
• Inadequate technical know-how in the company
• High Cost to on board expertise and cost of the project.
• Scalability of the Data Model
• High percentage time spent on Data Preparation
• Difficulty in dealing with Unstructured Data
• In-adaptability in ever changing technology
• Much time spend to get insights and Outcomes
Artificial Intelligence As a Services (AIaaS)
Machine learning and Deep learning involve feeding data into machines, which then decide the best course of action based on that data without human intervention. That is self-learning algorithms, the machine essentially learns from the data they are given and decides what to do next. The Cognitive computing is to stimulate human thought processes in a computerized model. By using self-learning algorithms, the computer mimics the way the human beings brain works. The cognitive computing market are the major factor that boost the growth of the AIaaS.
TeleAce Data Analytics AI tool will work on Structured and unstructured data and help customer to
decipher insight. Extract value from reams of information to perform enhanced business objective such as
1. Cost Reduction
2. increase in Productivity
3. Uncover hidden ``obstacles`` that interfere to Business process and operations
1. We connect customer’s structured and unstructured data to get insight and reveal unknowns.
2. Our Social Media Analytic AI & Text Analytic AI extract sentiment from unstructured data such as email, customer reports and social media; by merging with structured data to build a predictive Analysis
3. We provide better Insights than customer get from the structured data alone.
4. We help customer to perform Financial Analytics using our advanced AI tools to understand customer past and present performance and make strategic decisions.
5. Discover patterns and insights using AI Machine Learning, AI Deep Learning and NLP, use pre-built AI models, such as Customer Loyalty, Segmentation, etc. Perform enhanced free-flow search like- ``Customer Loyalty in any industries``.
6. Our Augmented Artificial Intelligence as a Service, will run on premises keeping Data Sovereignty in tack (Security)