What is data collection?
Data collection is the process of gathering and measuring information that is of interest to the company. It puts in place systematic and automated processes that allow to answer the questions of the users. Data collection solutions also allows the verification of certain hypotheses and the evaluation of results. Many business processes require reliable data sources that result from the accumulation of validated data. Collected data can be quantitative or qualitative. Their integrity is crucial to validate their usefulness. A data collection tool must be as reliable as possible to minimize the possibility of error in the production of results.
Four types of data collection methods
There are four types of data collection methods: observational, experimental, simulation, and derived. The type of data affects how it is managed. For example, irreplaceable data require specific backup procedures of raw data. In the case of data generation resulting from a fusion of other data sources, data corruption can be a central concern. The data collection solution must implement strict control procedures to address these potential problems.
Data collection solution can ingest raw data and transformed data source
Data collection tools are fed with observational data. Collected data is harvested gathering data field from the company's operational, financial, administrative, and other activities. ERP and CRM systems are the source of most of this observation collected data. The data collection software can ingest raw data from these systems or ingest data already transformed by them. Increasingly, sensors measure the company's physical operational activity to produce data in real time. Mobile data may come from a production line or a building and its communicating modules thanks to IoT for example.
How to collect data?
Data collection can be done both online and offline. In the first case, it is a matter of capturing in real time information of interest disseminated in raw data streams. This could be orders placed in real time by customers on an e-commerce site. In the second case, where the data source is not connected, the acquisition of raw data is done by extracting information already stored.
For example, salespeople can extract important mobile data from their customer meeting databases to prepare their commercial reports.
Companies that want more responsiveness and agility in their business processes often turn to mobile data collection. This data, often generated by mobile data collection, provides quick insights into changing operational situations. It is usually fed into the company’s decision-making systems as real time data for continuous monitoring and even predictive analysis. This connection between data collection software and business systems such as CRM and ERP is automated by means of software plugins to collect raw data. This mobile data collection stream is tightly coupled with continuous machine learning systems to update the whole company’s data pipeline using MLOps.
One of the main benefits of data collection solutions is the ability to collect data offline even while on the go. These offline features of the data collection platform allow users who work in locations where the internet is unreliable to store a backup of their collected data on their mobile device and download it as soon as a network connection is available. The data collection tool then supports the transfer and reconciliation of the data with its storage locations in the company’s digital infrastructure.
What to do next with collected data?
The data collection platform is a piece of software that provides a unique and reliable source of truth for enterprise-wide information systems. As such, it ingests data by transforming it into the desired formats. It also avoids duplication and ensures, as far as possible, that certain errors made during data entry in the fields of the enterprise software are corrected. The collected and validated data are then available for use with visualization software and for analysis to make predictions. LOAMICS is a leader in its field thanks to this unique and tight integration of intelligent data collection solutions and the various AI-based platforms that process them.
Providing customized 360° visualization
As any data scientist or AI engineer will tell you, they spend most of their time building data sets. The cleanliness, reliability and interpretability of the data depend on the reliability of the models they build.
Our LOAMICS-DataCollect platform guarantees you the best sources of information for all your downstream processing. It is the cornerstone on which our suite of tools is built. They quickly transform your data-intensive business into a digitalized, data-driven business whose growth is based on this data.
Once ingested in real time, this unlimited volume of data in all formats is transformed into a unique, homogeneous, and value-creating source of truth. Our LOAMICS-DataLake offering exposes it via metadata that makes replicating your proprietary data unnecessary.
Your information is ready to be used immediately for analysis and artificial intelligence. LOAMICS-AlgoEngine connects and analyzes it in real time. You generate customized insights available to all users in the company. You create your own library of intelligent algorithms, real growth levers, which increase your industrial performance.
Collecting, enriching, and analyzing data to offer a unique view of the company is the task we have set ourselves. With the LOAMICS suite of applications, enter the age of the company that considers its data as an integral part of its capital and its industrial and commercial resources.
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