data management software
Iryna Kravchenko Iryna KravchenkoChief Editor

5 best data management software solutions for your business in 2022

Ours is a profoundly digitalized age. Millions of high-tech machines all over the world generate 2.5 quintillion bytes of data that can deluge individuals and organizations by their volume and versatility. Whereas for ordinary people, such an influx is a cause of bewilderment or annoyance, for businesses, it is a threat to survival.  

Modern enterprises produce and process a huge portion of this data ocean related to their customers, internal workflow, marketing strategies, goods and services they produce, etc. Given the amount and complexity of such data, managing this mass manually is out of the question. Luckily, the source of the problem offers its solution. To put it simply, digital technologies that generate and transmit the lion’s share of data have brought forth data management programs and tools. 

You may find it useful: Data warehouse and ETL consulting services

Data management solutions: How can they help you?

Also known as data center management software, this technology is honed to extract data from multiple sources with subsequent processing. Such processing embraces sorting out the data (identifying the relevant information and sifting away the unimportant one), transforming it to be presented in digestible formats, and integrating various pieces of it to play well with each other.  

In fact, such solutions act as a comprehensive database whose primary storage mission is augmented by various data management functionalities. The latter become highly instrumental in handling interactive queries from a range of endpoints, gauging risks of shop floor processes, comprehending user behavior, mapping out marketing strategies, and performing other coal-and-ice activities businesses are engaged in. As a result, onboarding of enterprise data management software yields a 12% growth in revenues which proves the efficiency of this technology for quick ROI. How is that achieved? 

Benefits of complex data management software

When properly employed, database management software can usher the following boons. 

Data management software benefits

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Data management software benefits

Data consistency 

As a rule, organizations make use of numerous data sources obtained via multiple channels and stored in different repositories. For instance, one endpoint has the client’s email, another – their phone number, and the third – social media profile. In such a case, finding a piece that you need is quite a challenge. Customer data management software will help to keep all the client-related data in one place and see to it that the info is accurate, relevant, and accessible for all stakeholders. 

Data integration 

Thanks to data management solutions, employees from all parts of a company will have a single version of the truth at their disposal. Such integration efforts will allow not only to standardize vital shop floor data but also remove redundancies and segment data sets into custom workflows. 

Enhanced data security and privacy 

With numerous endpoints in play, it is often hard to provide enterprise data security. Data management applications installed on the mobile devices of employees help to protect the personal and financial data of clients as well as critical internal information of the organization. Monitoring the enforcement of privacy compliance regulations becomes a breeze too. 

Increased productivity 

Since the personnel can access and exchange data lightning-fast, they will waste less time on technical issues and focus on more high-value activities and strategic endeavors. Besides, the elimination of manual data handling leads to fewer mistakes, hiatuses, and other bottlenecks caused by human factors.  

Improved decision-making 

Having the entire scope of high-quality information at their fingertips, managers can make data-driven decisions better. This relates both to tasks at hand and strategic planning initiatives alike.  

Being aware of such unquestionable merits of data management software, entrepreneurs eagerly hunt for ready-made solutions of this kind. 

The list of 5 best data management software solutions: The DICEUS choice

As a seasoned offshore software development company, DICEUS considers one of the following data management solutions to be a pretty solid choice among the sea of options. 

Best data management software solutions

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Best data management software solutions

Oracle RDBMS 

Being a leader in the niche, this object-relational solution gets better with every new update. The latest one is cloud-based that supports all current Windows, Linux, and UNIX versions. Such progress also involves its size becoming smaller, performance swifter, and storage volume bigger. A perk worth pointing out is the ability it extends to users to create partitions, thus improving your control over the data.  

The only downside to this heap of merits is the price which may be forbidding for cash-strapped startups and small businesses. 

Amazon RDS 

This tool enables users to process huge workloads in a single database. Moreover, you can reach out to third-party databanks, including MySQL, Oracle, and Microsoft SQL. Another asset Amazon Relational Database Service offers is its utmost security. It is achieved via a dedicated connection and an inbuilt data backup and recovery feature. The payment scheme is rather cost-efficient since you pay on-demand only for the resources you use.  

Among the shortcomings of this solution, one must mention its narrow auto-scale power and inability to check server logs because of the absence of access to the physical server. 

Razor SQL 

Supporting over twenty programming languages, the solution is quickly gaining on the two behemoths mentioned above, thanks to its functionality roster. First of all, it allows you to build, update, or delete SQL statements in chunks whenever your needs require it. Second of all, you can leverage it to check tables, schemas, columns, structure indices, and even unidentified keys. Third of all, its import options are extremely wide, letting you incorporate excel spreadsheets, fixed-width, and extended data files. 

These major perks are supplemented by the automated copy and selection mechanisms tailored for different data types, the availability of both pre-set and custom templates, and the capability to compare data and queries across multiple databases. Plus, it won’t make a hole in your pocket with its affordable annual price of $99.95. 

The only thing that can hold back the eager-for-fast-result entrepreneurs is Razor SQL’s quite lengthy installation and configuration procedure. 

Informix dynamic servers 

It is named dynamic, not for naught. This tool is highly scalable, flexible in operation, and can process data in a parallel multithreaded mode. It works with Windows, Mac, and UnixLinuxx operating systems and supports Internet Protocol, while the solution’s Online Transactional Processing is an undeniable force.  

The vendor offers several pricing plans depending on the amount of data you will work with. So, you can choose one that fits both your workload and wallet size (although the top scheme is not chump change). 


There are two chief features of this solution that differentiate it from the ones that we mentioned. The first is its open-source nature, which means that using Altibase won’t cost you a penny. The second is its hybrid storage capacity that encompasses both in-memory facilities and the disk-resident database. These, together with the scale-out technology and sharding options, make the software one of the most popular solutions in the business world, employed by more than 650 companies in their 6,000+ use cases. 

Being superb boxed solutions, the above-mentioned (and any other, for that matter) tools fall short of bespoke data management software. 

Custom data management software advantages showcased

Specializing in data science projects, we at DICEUS realize that custom database management software beats canned solutions in several aspects. 

Custom data management software benefits

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Custom data management software benefits

Long-term cost efficiency 

Although building your own solution is definitely more expensive, you will find this a good investment that will pay off in the long run. First of all, with custom software, you pay only once. A boxed solution will require renewing your license every now and then, running up the total cost to quite a considerable lump sum. Secondly, in a canned solution, you are likely to get a roster of functionalities that you don’t need and will never use, but you buy them as a part of the deal. In the bespoke data management solution, you will pay only for what you require.  

Better integration with other software  

Since you are free to build a data management solution, ensure it plays well with all platforms and applications you use. In a canned solution, you are likely to find yourself in a situation where your CRM or ERP users can’t see the data in the acquired database management tool. 

Opportunity to fill It with features you need 

The selected canned solution is always a tradeoff between what you need and what you get. You have to resign yourself to the roster of in-built functionalities or pay extra bucks for add-ons (see Point 1 above). When you commission a custom database management tool, you are free to choose the features it is going to have.  

Broad scalability 

After some time employing a boxed data management solution, you may discover that you have outgrown its potential and start looking for a new one (and fork out a pretty penny again). While building bespoke software, you can envisage such prospects and make scalability provisions for the solution in case your business expands.  

Competitive advantage 

A runner wearing sneakers that are too large or too tight on him can hardly be expected to win the race. But with a database management tool that is a perfect fit for your organization, you have the edge over your rivals utilizing boxed software and can outrun them in a cut-throat competition symptomatic of the modern market in most industries. 

Whether you opt for a boxed or bespoke data management solution, you should know well what functionalities to look for.  

Must-have features of data management software

Most canned solutions of this kind contain the following characteristics. 

Data quality control. This functionality enables you to detect and fill in gaps if those occur within your data, as well as remove redundant information that eats up storage space and confuses analytical efforts. 

Data change control. You can see when and how any piece of data was modified by receiving corresponding alerts. 

Data organization. Unstructured data is hard to perceive and interpret. That is why a good tool stores all the info in a comprehensive catalog and gives you a choice of records, tables, objects, or other media to arrange your data hierarchically.  

Data durability. The last thing you want to see is the disappearance of the data from the system. That is why a solid data management solution should provide data backups to minimize data loss risks. 

Data security. Another unpleasant event that haunts your nightmares is data leakage, followed by imminent financial and reputational damage. To forestall system compromising, a database management tool must utilize tokenization, encryption, access control, and other security mechanisms. 

Workflow automation. Machines are meant to relieve humans of elementary or repetitive tasks, and most data management solutions do just that by automating many data processing jobs. 

Custom features

These are bread-and-butter functionalities found in an average canned data management solution. And if you decide to build a bespoke tool, you can augment this basic list with some more features. 

If such features seem attractive to you as a part of a data management solution, aim for a customized one. However, to develop high-end software of this kind, you should know how to go about it.  

How to build a top-notch custom data management solution

Over the years, our competent experts have arrived at a foolproof algorithm for developing bespoke solutions. 

How to build custom data management software

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How to build custom data management software

Step 1. Discovery and research 

This is a preliminary phase that lays the foundations of the future project and ultimately determines how successful it will be. Discovery starts with identifying the specific problem the solution is going to address. Then, interviewing CEOs, managers, and other stakeholders, you should clarify the business objectives of the project, its scope, basic functionalities, and deliverables. Perhaps, the customer has a legacy solution that needs revamping, so you should fathom its inadequacies that must be remedied and fortes that are worth keeping. 

After that, the research steps in. It covers two fields. The first relates to the prospective users whose expectations are identified via polling and whose preferences and tastes are explored through other research methods. The second procedure is a comparative analysis of competitors’ products to expose their strengths and – more importantly – drawbacks which you should turn into a competitive edge by mitigating them in your counterpart tool.  

Step 2. Getting to grips with the technical side  

Being aware of all prerequisites, you can determine the technical side of the solution-to-be, including its architecture, infrastructure, dependencies, third-party integrations, and APIs. Besides, you should decide what tech stack you will use to build all those components. 

Step 3. Embracing the team 

The composition and the size of the crew largely depend on the project scope. The kernel team is to include a software developer, a UI/UX engineer, a QA specialist, and a project manager. However, the nature of each data management solution may require augmenting the crew with an additional workforce or specialists with specific skills. 

Step 4. Selecting project management methodology  

Working with a remote team, it is mission-critical to set up a communication plan that will pinpoint the mode of development (Agile or Waterfall) and guarantee smooth interaction between stakeholders. The latter must agree upon the rapport channels and meeting schedule comfortable for both sides. 

Step 5. Evaluating the cost 

Now when you know all factors that condition the cost (including the chosen pricing model), you can calculate the budget the customer will have to allocate to see the project through.  

Step 6. Coding 

With all preparations over, you can get down to the actual development hammer and tongs. This is the core of data management software creation and the longest stage to accomplish.  

Step 7. Testing 

When the product is built, you must make sure it operates according to expectations. The QA team does it by performing several kinds of automated and manual tests, such as systems, unit, integration, user acceptance, etc. 

Step 8. Support and maintenance  

A reliable vendor doesn’t call it a day even once the finished product is delivered to the client. Developers monitor the deployment and first months of its usage, give advice or lend a helping hand once a problem arises. 

When implemented properly, this algorithm will yield a high-quality result. 

Examples of data management software

We at DICEUS have successfully delivered a number of database management products. Let’s have a look at two of them.  

In the school project for Computopic, we aspired to create a centralized data management system supposed to streamline and upgrade event and lesson scheduling, messaging, news sharing, exams management, curriculum editing, and other aspects of the private school routine.  

The data management platform that we built has various tools for different user roles (teachers, administrators, students, parents), dynamically updates the content while saving changes, and can be accessed via a responsive mobile app. It is extra-secure with its account authentication mechanism and has a user-friendly built-in messenger.  

Another product of this type was the HCM data management system. It is an enterprise all-in-one app whose purpose was to accelerate and promote data management by automating a huge chunk of personnel routine.  

We created a universal solution that was instrumental in structuring the heavy information flow (including data from third-party resources that is automatically downloaded to definite locations within the database), storing it in convenient formats, and delegating repetitive tasks to the AI. Besides, it enables customized report management, prioritizing data downloads, and viewing relevant regulations. Its separate dashboards allow different capabilities for certain roles of users who can access the data via multiple endpoints. 

How DICEUS can assist in making your data management easier

As you can see from the described case studies, database management tools find ready applications in many domains where far-sighted business owners realize all the value-adding perks this software promises to their companies.

DICEUS has sufficient competence and experience to tackle a data management project of any complexity in any industry. By implementing data management, you will turn your company into a data-driven enterprise.


In the data-driven business world of the 21st century, efficient handling of information is a key competitive edge that can help companies to increase productivity and facilitate routine workflow. By onboarding high-profile bespoke database management software, entrepreneurs can significantly streamline data handling and automate a fair share of their shop floor activities.  


What does data management software (DMS) mean? 

It is a digital technology that streamlines and facilitates working with data. 

What is data management software? 

This solution functions as a database with a set of tools that enable amassing, storing, structuring, transforming, prioritizing, and integrating enterprise and customer data from various sources. 

What is master data management software? 

Such solutions build and manage a centralized index of record of master data, support its linking and synchronization across versatile sources, aren’t industry-specific, and can be implemented by non-tech personnel.  

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