Understanding Operational Data Store, Data Warehouse, Data Lake, and Data Mart

Daily, businesses produce large volumes of data from various sources. The data is important because it can help the business make crucial decisions to help improve performance and service to its customers. As data quantities increase, companies get a challenge for storing and processing it to its advantage.

There is a wide option of storage and processing tools that a business can use but they must understand each option before making a choice. The main guiding factors to their best choice will be data type, its scope, and use. A business may opt for any of the following choices.

Operational Data Store and a Data Warehouse

Sometimes comparing operational data store vs. data warehouse can be complicated because they share a lot of similarities, mainly because both move data from multiple sources and consolidates it into one place. However, they have main differences, too, like data scope and volatility.

An ODS only stores current data that a company can access for real-time analysis. It may at times be used as an intermediate between an information warehouse and a transactional database. An ODS is used for data consolidation, troubleshooting, real-time reporting, and system integration.

On the other hand, a data warehouse collects information from multiple sources like the sales department, human resources, accounting, online sales, etc., and consolidates it into one big storage. From there, users can do queries and analyze data, report, and get business intelligence. It stores current and historical data from multiple transactions within several business units.

The main differences between an ODS and a data warehouse are as follows:

The scope of information: Data on ODS is updated every time new information is processed and a business can only retrieve what is current. A warehouse does not overwrite old data with new but integrates it to create a bigger data volume based on history.

The volatility of information: ODS data changes values all the time in a bid to keep its available information current/real-time and this makes its information highly volatile. Anytime data is updated, its old data is lost. Information stored in a warehouse is less volatile because all its historical values are retained.

Opportunity for data growth: Data on ODS does not grow because every historical data is overwritten with new data, whereas that on a warehouse keeps growing as the business grows.

Data lake

As technology changes, like in the recent growth of blockchain technology, the need to store larger and accurate quantities of data arises. A data lake becomes an excellent tool because it can provide greater options for data queries.

A data lake is capable of storing larger quantities of data and includes any type of information a company feels might be useful in the future. As a result, this tool can store data in its exact format like PDF, Corel, word, photo, video, JPEG, or any file format a company chooses.

At the time of retrieval, the information will be retrieved in its original format and used for analysis or reporting, although a more complex technology is required to store and extract data from this system. It requires users who are more conversant with various programming languages to effectively use information from a data lake.

Database

Databases are the oldest forms of storing data and they are still widely used today. Companies store information in rows, different columns, and tables. They provide fast access to data using various data management tools.

A database can be used to track customer behavior and recommend products based on their needs. They can also be used to process online orders or payments. A company’s database is considered ACID-compliant when it’s durable, consistent, isolated, and atomic.

Data Mart

A data mart can be likened to a data warehouse but the only difference is scope. A mart is smaller and can only hold a smaller amount of data at a time. Data contained in a data mart can be restricted to a specific business department like sales, purchases, HR, delivery, or accounting.

It helps that specific department access portions of information they need fast and process it for its internal use. To feed a data mart with information, a business needs to create data tables, feed them with information and set relevant access rules.

A data mart can access information from a single/independent entity or from a dependent entity where data from another source like a warehouse is divided into subsets for access by specific departments.

Data Hub

A data hub provides more flexible and tailor-made information solutions to a business. Sometimes a business might not find every information stored in various tools like data lake or warehouse useful for processing to provide important information.

This creates the need to clean the data, refine it, group older data and newer ones separately, remove duplicated data, and do security tests. The data hub does all these roles and provides insights for information sharing and collaboration with a business.

It helps integrate data from several sources and make it easily accessible and usable by the specific business department. The data hub is programmed according to unique business needs such as different reporting methods, forms of analysis, current models, and data access rules.

Criteria for choosing the right data storage tool

Every amount of data is important in helping a business make decisions and improve customer service. It helps businesses make strategic goals and implement them depending on needs and service gaps. Because of its crucial importance, businesses use data as the baseline to measure progress, setbacks and to launch new strategies.

Choosing the right storage type will help a business eliminate hitches in the data flow from its multiple sources to storage, retrieval, and processing. The criteria for choosing the right storage can be guided by several factors.

Speed: You must choose a system that has fast execution speed.

Easy to use: Choose storage that can easily be used internally according to business need because some systems will require experienced programmers to execute.

Secure system: Security is a primary factor to avoid data breaches.

The flexibility of pricing: Some systems provide monthly flat-rate subscriptions while others have pay-as-you-use options.

Accessibility: You require a storage tool that is easily accessible anytime.

Data type and scope: Some storage can only store data in a single file type, while others allow multiple file types storage. Choose a system that can handle all business data quantities.