The amount of data being collected by each company every day may be enormous. You use it to get insights for your business, but also to perform basic tasks and run processes in your company. Simply, there is no business without data to manage and store. There are many ways to store a company’s data. Choose the one that suits your needs best.
Some data you collect isn’t crucial for your business to operate. A lot of it is useful though, and analyzing it can improve your decision-making process or increase the quality of your services and products. There is also data without which your company wouldn’t be able to function correctly – each business has it and needs to store it somehow. Data analytics is necessary for a company to grow – that is why you need to choose the best way to store and secure your data.
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Things to consider when choosing how to store data
Securing and storing your data is very important. Think carefully before you choose the proper technology for your company. There are many criteria you have to analyze.
Functional requirements for your data store
First of all, you should think of the data you’re about to store. What will be the data format and how large will the entities be? It is good to know how much overall storage space you will need. It can be maintained as a single document, but that is not the only choice you have, as it can also be split into multiple forms. You have to decide whether relationships among the data are important and what kind they are (one-to-one, one-to-many or many-to-many). There’s a lot more to it – the choice of consistency model, concurrency mechanisms, if your data storage solution will have to perform ETL tasks in order to move data to other stores, how long your data lifecycle will be and if you require any specific features.
When it comes to deciding about software, you should always remember about the performance and scalability of the systems you’re going to purchase. You might have specific performance requirements for storing some data. What time for querying and aggregating data do you find sufficient? Don’t forget that it is highly possible that your business will grow in the future – bear that in mind. Try to predict how large your data store will need to be in the future.
There are many types of encryption you can use. It is crucial to ensure the safety of your customers’ and your business data. Data leaks, damage or theft can ruin your company. Protect your vital information by using the best authentication mechanism available. You can also set access restrictions by enabling access to data only from specific IP addresses, subnets and applications. Some other important matters are the kind of backup and your capabilities to restore lost data.
You can choose managed services (outsourcing of services) or engage your in-house team in managing the process of storing data. Using each piece of software requires particular skills like knowing specific programming languages, operating systems or modern technologies. If the software has good customer support, you could try to leave it to your in-house specialists. You have to decide then if you prefer a proprietary or an OSS licence type data store. In other cases, you can benefit from managed services. This is very often a better time and cost saving solution. A company can decide from many types of solutions, among the most popular are:
- IaaS (Infrastructure as a service) – you get a physical infrastructure for your business, but you still require a team of experienced specialists to maintain it.
- PaaS (Platform as a service) – except for the infrastructure, you’ll also get a platform – OS and basic tools you need for future development.
- SaaS (Software as a service) – this solution gives you all you need to operate (ready-to-use programs and applications) and tools for development.
In the end there will always be costs that you have to consider when deciding what kind of data storage method to choose for your company. Sometimes deciding on managed services is a way to reduce operational costs. Compare the various solutions before you make your decision.
Types of data stores
This term is used widely when it comes to discussions about data. In databases, information is stored in tables, columns and rows for easy processing. That storage is managed by the DBMS – database management system. There are relational (SQL) and non-relational (NoSQL) databases. A relational database is generally said to be the most common kind. This is a type of database which enables users to access data presented in relation to other pieces of data in the same storage.
A different type of database is the operational data store (ODS) – it provides a snapshot of the latest data for the user from many transactional systems. This can be then used for preparing operational reports. The ODS will allow your company to gather up-to-date data from many sources in its original format for reporting purposes.
Is this the best way for your business to store data? You could invest in databases instead of other solutions if quick and frequent access to data is what you value most. If you work in an industry which relies on data and requires its fast processing (e.g. transport, like airlines or train networks, which have to process tickets online), a database is a good choice.
A Data Warehouse is a multi-purpose system – it can be used by various companies in any industry. What is special about it, is that the data warehouse can retrieve information from various sources in your organization. This type of software is capable of collecting data from numerous applications for later storage and management. As the data is copied from the source into the data warehouse it can be immediately analyzed.
Data warehouses usually use SQL in order to query the data, exactly like databases. Data is stored in tables and organized by types with keys, indexes etc. and can be used for creating reports or for analytical purposes. Data in warehouses is updated and users can check how data is changed.
This is a repository for summarized, subject-oriented data from the data warehouse. This solution may suit specific users and teams within your organization, although it is hardly a type of tech that could serve all of your employees. A data mart allows some employees to access specific types of data stored in the data warehouse, among other kinds – for example, accountants can use it to get financial data and marketing specialists can gain data needed to create a new strategy. In short, it is designed and developed for particular business tasks.
There are 3 types of Data Marts:
- Independent Data Mart – which doesn’t rely on an existing data warehouse. Data is taken from original sources when analysis is needed.
- Dependent Data Mart – is connected with an existing data warehouse and when users want to run analysis, they can access only specific pieces of data from the data warehouse.
- Hybrid Data Mart – gets the data from external operational sources and data warehouses.
All kinds of raw data generated in your organizations can be stored in a data lake, so any user that has been granted access can retrieve relevant, needed data. This storage is done without any processing though – each piece of information is like a small drop in the lake. Everything is in there – structured data, chat logs, e-mails, images, documents, videos. So what is the difference between data warehouses and data lakes as they can both store large amounts of data? A warehouse stores processed data, while a data lake stores raw data as well.
What is the problem with data lakes? As they grant more flexibility to a user, they’re also less secure. A company may need a data scientist to use data lakes. They may be useful though for big organizations that have to analyze a great deal of data to improve their business.
There are different ways to store and process data. Everything depends on what you need. Some data storing solutions can be better for you and others may cost you a lot of time and money. Before you choose your software, we encourage you to consult with our experts. Contact us – we can analyze your company’s needs and suggest some efficient data storing approaches for your business.
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