What is a DataLake and how does it work?
It’s an innovative approach: ELT (Extract, Load, Transform) compare to the older process of ETL ( extract, transform, and load)
A DataLake is a centralized storage location that contains Big Data in a raw and granular format. It comes from many sources in many formats. A DataLake can store structured, semi-structured or unstructured data, which means that the data can be kept in simpler and more flexible formats for later use. When importing data, the DataLake associates it with identifiers and metadata tags for faster retrieval. Searching a DataLake is also faster because you only need to browse the metadata, not read the entire contents of the files. The term Data Lake implies that the data is stored in bulk and in raw form. In traditional Data Warehouses, clean and processed data is stored.
Read schema vs. write schema
The schema of a Data Warehouse is defined and structured before storage; it is applied while writing the data. That of a Data Lake is not predefined, which allows it to store data in its native format. In other words, in a Data Warehouse, most of the data preparation usually takes place before processing, whereas in a Data Lake it only takes place when the data is used.
Accessibility and flexibility
With a Data Warehouse, you need to allow not only time to define the initial schema, but also significant resources to modify that schema whenever business needs change. Data Lakes are very adaptable to change. As storage capacity requirements increase, it is easier to scale the servers in a Data Lake big data cloud cluster because the raw data is not organized in the cluster.
Why use a Data Lake solution?
The DataLake paradigm has many advantages over the traditional Data Warehouse.
There is a real warehouses data lakes tradeoff. With DataLakes, data is stored in a native way and is therefore easy to extract and process. It is totally possible to use any kind of open-source data pipelines.
LOAMICS-DataLake fully exploits this paradigm to put your single data source just a few clicks away from your users.
A Data Lake operates on a “schema on read” basis, which means that there is no predefined schema into which data must be imported before it is stored. Only when you access data for processing it is analyzed and adapted into a schema if necessary. This feature saves the time needed to define a schema. This is usually exceedingly long and depends on both the volume of data to be processed and the complexity of the schema. A Data Lake allows to store data as it is, in any format. This simplification allows data scientists to access, prepare and analyze data faster and with greater accuracy. For analytics experts, this vast pool of cloud data available in non-traditional formats gives them the ability to access data for various use cases such as consumer sentiment analysis or fraud detection.
Data Lakes are not comparable to Data Warehouses. In fact, they have some notable differences that can be significant advantages for some companies. This is especially true at a time when Big Data, machine learning and their processes are migrating massively from on-premises solutions to the Cloud. Typically, Data Lakes are configured on inexpensive and scalable standard server clusters. This type of configuration allows data to be stored in the Data Lake without having to worry about available storage capacity. If these clusters can be deployed on site, the trend is to place them in the Cloud. This evolution is logical when you consider the advantages provided by hosted data services (redundancy, fault tolerance, security, geo-localized replication, etc.).
LOAMICS-DataLake software benefits
LOAMICS-DataLake is capable of handling large amounts of structured, semi-structured or unstructured data. Once collected, the data is placed in clusters located on the customer’s cloud instances. LOAMICS-DataLake ensures a real virtualization of all the data in the Data Lake. The data is then exposed and made available to all processes, including those in AlgoEngine, which feed analytical applications, reports and dashboards. LOAMICS-DataLake is fully integrated with our other software solutions.
The following benefits can be attributed to it:
- Data automation
- Microsoft Azure Marketplace
- The LOAMICS solution on 4 levels
- European hub Gaia X
- MyDataModels' partner
According to a Forbes study, Data Scientists spend about 80% of their working time preparing the data they will work on.
These skills are monopolized by repetitive and boring work, taking valuable specialists away from the tasks they really excel at. With LOAMICS-DataLake, data preparation is fully automated to an industrial standard.
Data professionals can now focus on their analytical work and on feeding artificial intelligence models.
Since April 2021, LOAMICS data lake solutions and data lake tools are available on the Microsoft Azure Marketplace.
Microsoft’s cloud is recognized as the most flexible for data warehousing, thanks to its architecture that facilitates the establishment of Data Lakes. Azure is also the most renowned Cloud for its Artificial Intelligence offerings, notably thanks to its Cognitive Services.
All LOAMICS customers can now deploy their Data Lakes on Azure and benefit from its great scaling capabilities, agility, and reliability. They also benefit from all the advantages of a Microsoft Network Partner specializes in Big Data Analytics.
The LOAMICS solution on Azure Cloud for your Data Lake established at 4 levels:
- It is a plug and play flash solution ready for data analytics. Customers access their cloud Data Lake as soon as they are connected to the Cloud instance. You do not have to wait weeks or months to integrate them into decision-making processes or if you want to include them in your reports.
- Customers retain full governance of their data; they do not need to export it for use thanks to Platform as a Service (PaaS) operation. The upstream and downstream processing of the data sources is done in a totally automatic and fluid way.
- The integration of data is unlimited thanks to the strong interoperability of LOAMICS-DataLake. Whatever the sources, systems or protocols used for your real time data, your Business Intelligence applications, your visualization tools, and all your other applications can use the information from the Data Lake platform. This connectivity is full of all Microsoft Azure services.
- Your data science specialists do not have to prepare the data and can focus on higher value-added tasks, such as envisioning disruptive machine learning models, to gain productivity and performance. Data Sets are created automatically in real time by the Data Lake software, and their use cases are unlimited. Whatever the size of your company or the type of your activity, you can be sure to significantly improve the return on investment of your data placement on the LOAMICS-DataLake.
LOAMICS has joined the European hub Gaia X which contributes to strengthen the sovereignty and governance of European data.
The users of our Data Lake storage solution are thus assured to meet the requirements of the RGPD.
They can operate freely on the entire European market. This gives them a recognized competitive advantage in terms of commercial openness.
It is conferred by a secure sharing of data and the creation of a European data ecosystem of industrial quality.
This ecosystem can be used with confidence by even the most advanced research teams.
By partnering with MyDataModels in June 2021, LOAMICS is taking another step towards much faster and more powerful Big Data analysis capabilities.
This will enable marketing strategy decisions to be made at a level unmatched in the Big Data This partnership simplifies complex data management processes, reduces the level of human intervention and strengthens data governance and sovereignty.
Data is instantly accessible and easily lined up when desired.
Discover our other software
LOAMICS-Suite totale is composed of 3 modules including LOAMICS-DataLake.
In addition to this data management application, LOAMICS-Collect is used for data collection and LOAMICS-AlgoEngine for data processing. They are all part of a specialized and optimized pipeline that brings Big Data within the reach of companies of all types and sizes. This suite is a true artificial intelligence gas pedal that enables decision making based on data mining and self-service analysis. Once collected, the data is cleansed and made available in the Data Lake as a single data source. Regardless of volume and format, it is easier to access, analyze, freely cross-reference, and exchange.
Your organization can finally move from being a simple data user to a real business built around and on its data.
Our other software
01 Data collect
Collect and ingest raw data in real time (regardless of the volume, sources or format), to be very simply transformed into homogeneous, efficient and valuable enriched data ready for data visualization and first levels of analysis.See more
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