Data Collect
Our data collection software is a computerized system for harvesting and storing electronically accessible data. This data collection solution has several advantages: it does not require preparation nor planning prior to the data collection process and it ingests raw data that can be used immediately for building reports to produce analyses and update dashboards. Our data collection tool is an efficient substitute for data entry. Real-time data collection serves as a data source to meet the data visualization needs of digitalized companies.
Data Collect, a unique solution on the market
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 answer user question. Data collection solutions also allow for the verification of certain hypotheses and 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 for 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 solutions can ingest raw data and transformed data sources
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 observed 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. Real-time data may come from a production line or a building and its communicating modules using IoT for example.
Data collection
Data collection can be done both online and offline. In the first case, it is a matter of capturing information of interest in real time that is disseminated from raw data streams. This could be orders placed in real time by customers on an e-commerce site. 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 real-time data from their customer meeting databases to prepare their commercial reports.
Companies that want increased responsiveness and agility in their business processes often turn to real-time data collection. This data provides quick insights into changing operational situations. It is generally 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 real-time data collection stream is tightly coupled with continuous machine learning systems to update the company’s entire 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. Offline data collection platform features 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 to correct any errors made during data entry. 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-Data Collect 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.
LOAMICS-DataLake
Once ingested in real time, an unlimited volume of data in any format is transformed into a unique, homogeneous, and value-creating source of truth. LOAMICS-DataLake 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 can generate customized insights available to all users in the company. Create your own library of intelligent algorithms, real growth levers to increase your industrial performance.
LOAMICS suite
Collecting, enriching, and analyzing data to offer a unique view of your company is our goal. With the LOAMICS suite of applications, enter the digital age and allow your data to be an integral part of your capital industrial and commercial resources.
Discover our other software
01 DataLake
Provide access to all metadata (contextual data) in a key value system. Store and access proprietary data in a single, elastic, scalable system hosted within the organization. The data is ready to be exposed without the need to replicate. This data is prepared for analysis and artificial intelligence.
See more
02 AlgoEngine
Connect, process and analyze data in real time to generate insights that meet any end-user need within the organization. Manage a workflow and a library of algorithms that can be continuously enriched. Share knowledge by making available or exchanging the « right » data. Industrializatize the processes of connecting algorithms to the data for all your needs.
See more