Database, data analysis and data-oriented solutions
data location
With each passing second, the improvements are more significant than before, the basis of the improvements are all based on the needs that the owners of different businesses and industries achieve by analyzing their data. In the fourth industrial revolution and the fourth era of quality, which the world is in the middle of this road and we are at the beginning of it, data has become a fundamental element for the organization.
Every manager in the organization, from senior managers to operational managers, faces decisions every day that are sometimes routine and sometimes strategic. Decisions in the form of routine can cause loss of time or constantly require extensive analysis, which may cause the person making the decision to make a mistake in the analysis or not consider part of the data.
If these decisions are strategic, by ignoring part of the data or not considering the connections between the data, the analyzes are ineffective and ineffective.
Data-driven decision making
According to the fifth principle of management, decisions should be based on data, data-based decision-making leads to targeting improbable options and considering future scenarios with high certainty. Based on the data, managers can describe their events, analyze them, make decisions and finally predict what other events will follow by implementing the decisions made.
Machine learning and artificial intelligence
The 3 stages of description, analysis and prediction are the responsibility of human resources and the use of software and data collection systems, but if such events are repeated again, is it justified to spend time and money on decision-making?
The answer will definitely be negative, but how to avoid spending this money and time? Isn’t it better to entrust these actions to computers and teach them how to make decisions in such situations?
The gift of the 10th industrial revolution and the 4th generation of quality for industry and business is machine learning and artificial intelligence, which prescribe solutions for the organization based on description, analysis and prediction, and learn more by receiving feedback from the results and how They constantly improve their processing with these feedbacks.
Data integrity, effective analytics, computers with intelligence
Now let’s consider a system with the above elements in an integrated and efficient way:
- Adopt an efficient method for each source of data collection, using machine vision in the production line, using social network robots to analyze customer satisfaction and behavior, using data loggers for equipment performance status, etc.
- Establishing systems based on the Internet of Things, data recorded from equipment are connected to servers and computers using this technology, and the data is sent to users online for analysis and processing.
- Definition of learning algorithms for computers, the received data are stored and users identify the factors affecting the system based on their experiences and the use of statistical learning approaches and data-based decision making, machine learning algorithms and finally intelligence develop artificial
- Decision making, after developing learning algorithms, the computer receives and processes data and predicts possible decisions or scenarios for the occurrence of various events.
- Improvement in learning, a person gains experiences over time by receiving feedback from his surroundings. These experiences are obtained from data that is transformed into information for decision-making during the processing of the human mind, and making decisions and receiving feedback from the surrounding environment are experiences that change the human approach to the challenge. to give
The exact same thing is true for machines, with the development of learning algorithms, computers receive feedback after making a decision and strengthen their learning system.
Database services create databases
Database services Creating databases artificial intelligence machine learning Theme!
Data-driven troubleshooting
The data available in the organizations are identified and collected, and based on the problem defined in the organization, the consultant team, together with the experts in the desired field in the organization, describe, analyze and predict the problem (probable scenarios regarding appropriate actions). .
In order to create an efficient and effective analysis of business events, it is necessary to create appropriate bases in business intelligence. Business intelligence, a set of dashboards, is one of the important parameters of any business and key performance indicators, which can facilitate the process of analyzing business events to a great extent by visualizing data.
Regardless of the use of any tool to prepare for the use of business intelligence, the following steps must be taken to create it:
- Correct understanding of business
- Defining measurement criteria and formulating them
- Preparation of a suitable data collection plan
- Collecting data
- Data cleanup
- Performing the necessary calculations to prepare formulas for each index
- Create dashboards and set acceptance parameters
- Analysis and decision making
- Approving data collection periods to ensure the safety of the analysis process
Based on the problem proposed by the organization, data modeling and appropriate databases are designed for the organization, and based on the organization's approach to making a decision to create databases, data servers are created in the organization or in the Cloud platform.
In traditional data collection systems, data is collected in forms (electronic or physical) and each process prepares form fields according to the application data of its process, and this makes each process for The process itself prepares a database of data, and apart from the fact that such an action is very costly, on the one hand, it leads to the lack of integrity of the collected data.
The integrity of the data is important because the driving engine of the organization is an integrated system, and any incident in it will lead to changes in another part of the system, and for the analysis of this system, integrated data in a suitable platform and an efficient model are required. be used
In these projects, the consultant team describes, analyzes and predicts the issues raised in the organization with the cooperation of experts, and after making decisions and receiving feedback, develops machine learning algorithms in the learning engines of the organization.
Based on new approaches such as computer vision and machine vision, learning engines are connected to sensors that receive signals from the environment and collect data and turn them into feeds for learning engines and organize them based on learning algorithms. Machine decisions, actions and solutions are adopted with a high degree of certainty.
Data analysis consulting and data-driven solutions
Considering the relevance of these solutions in Iran’s businesses and industries, the organization should use these solutions based on the modern science of the world and localized according to its platforms in order to implement these approaches.
Noor Management Consultants Group (Modirfa) has expert consultants in the field of data science and a rich experience since 1987 with consulting in the field of deployment. Management systems The organization is by your side to put you ahead of the competition in the world by implementing new systems in accordance with the fourth industrial revolution.