Data is a strategic asset for many companies today. The better the data-analytic techniques appear the more valuable the asset becomes. It seems exponential growth of corporate data takes place nowadays. Data experts say that 90% of all data have been generated over the past few years. Data is crucial for such domains as Big Data, artificial intelligence, the Internet of Things, etc. Routinely collected data is the precursor for both improving customer services and facilitating operational activities of companies. Better decision-making results from proper data analytics. Research and development are totally dependent on data as well. Since data is too precious to neglect it, and its volume is continuously growing, efficient data management becomes a central point around which all enterprise operations start revolving. Not to turn the avalanche of collected data into a mess, various data management software systems are created.  

The challenge, however, is in choosing the most appropriate one for your business. Which selective criteria are worth applying to that? And what alternatives are available to select between? The present post addresses the issues within the scope of our expertise. 

Guaranteed software project success with a free 30-minute strategy session!

Get started

Data management solutions: What can they do? 

Imagine that none of the data management software exists amid the huge variety of data generated day by day. What troubles does any enterprise face in such a case? Fragmentation of data sets due to a non-harmonized approach to data management seems to be the biggest problem. Different storage systems, different processing methods, different validation procedures all consume a lot of extra labor and financial resources from a company.  

Some might argue that no universal “silver-bullet” data management software is possible to develop. There is some truth to that once only custom data management systems can be tailored to the exact needs and goals of each particular organization. However, modern data management applications are comprehensive, flexible, and scalable enough to be effective tools for the majority of enterprises from various segments.  

The cutting-edge software developments allow enterprises to rearrange data management throughout the organization by offering a good insight about which data is available and where, and how long the data is stored. But what matters most, they enable the enterprise management to share the right information with the right people at the right time. 

Such software widens operational opportunities of enterprises as follows: 

  • Getting access to data of different types 
  • Applying complex methods to data security 
  • Providing data integration 
  • Retrieving valuable analytics from data Enabling to manage files, objects, app data, databases, data from clouds and virtual environments 
  • Using various orchestrating tools to move data to where it can be stored in the most efficient way: primary and secondary storage infrastructures, data centers of service providers, clouds 

Benefits of complex data management software 

data management solutions

Either a set of separate software products or a single unified system can stay behind a data management platform. Complex data management applications provide unified command of data movements across the entire IT infrastructure of an organization. That includes, inter alia, automatic database backup, data recovery, operational control over all ongoing processes, and obtaining reports. 

Such complex platforms allow following a multi-cloud strategy to extend data processing to cloud environments. Fast migration to clouds helps refuse redundant in-house hardware to implement the most feasible methods of data storage.  

Some data management solutions are capable of archiving data automatically. The others use AI to notify system administrators when something goes wrong. They also can take remedial measures and resist attacks of various sorts. This is about automation of services that leads to optimization of all IT processes that in its turn results in freeing up IT staff, minimizing human-factor errors, and reducing downtimes.   

Organizations that use complex data management solutions achieve more in comparison with their competitors that don’t. They usually have shorter time-to-market periods, a better understanding of target audiences, and faster reactions to changes in demand. Advanced data management software solutions enable purifying raw data to get more relevant information while conducting a strategic assessment of enterprise data. 

Please read more data-related articles:

Look ahead: Cloud-based data management 

Managing data in clouds is a new modus operandi, a cutting-edge paradigm that provides innovative functions of data management under hitherto unprecedented scenarios. Enterprises have to follow this next-gen technology to keep pace with unavoidable digital transformation.  

Efficient allocation of resources, 24/7 monitoring of processes, transparent optimization of expenses, automatic data migration, advanced security, and improved danger resistance constitute just a fraction of capabilities inherent in cloud data management.  

The extent of data accessibility makes clouds incomparable to any traditional data management solution. The always-on accessibility implies total control over the whole body of information that an organization possesses. To be precise, the data flows appear fully manageable when round-the-clock access to data empowers data management tools to work with full force. 

The cloud service providers do their best to make their intelligent data management features intuitive and easy to grasp. Typical cloud infrastructure is rich with various automation solutions. They all share a common purpose of optimizing corporate data processing to let any customer organization become a data-driven enterprise.  

Data management solutions worth considering by any company 

Before choosing one or another data management software it is worth applying specific selection criteria to the offered functionality. Any decent data management system should be able to provide the following: 

  • generate reports with comprehensive data sets  
  • remove redundant info to keep data relevant 
  • collect data according to governing algorithms 
  • synchronize various sets of data into a common representative model (dashboard) 

The following data management software systems all can do what is mentioned above. Besides, their features go far beyond the basic selective criteria. 

Amazon Web Services

AWS combines various data management apps to offer something like a module structure of a data management system. In other words, customers can select between those options that meet their expectations best. This cloud-based data management solution can generate and aggregate a great variety of data for enterprises.  

The AWS services include transitionary data storage facilities (Amazon S3), SQL database analytics (Amazon Athena), continuous data backups (Amazon Glacier), data visualization dashboards (Amazon QuickSight), data warehousing (Amazon Redshift), etc. The set of services are created with large enterprises in mind. AWS is considered one of the most comprehensive data management solutions for the corporate sector.  

Microsoft Azure

Similar to AWS, Microsoft Azure offers many data management options to choose from. Azure covers different database types with multiple tools. Advanced analytics on what is stored in the Azure cloud go well with different data warehousing models. 

Azure provides services for various databases (SQL, NoSQL, and VM/SQL), analytics on raw streaming data sets (Azure Data Explorer), integration and synchronization with external systems, private cloud options, data storage capacities, etc. Like any other corporate-centric solution, Azure has a specific learning curve requiring some time to be grasped. 

Google Cloud

This is a direct competitor of both AWS and Azure. And similar to them, Google Cloud offers a set of data management services applicable to enterprise workflows. Google Cloud is a complex cloud-based workflow manager that consists of various components. 

The offered toolkit includes SQL query analytics and storage (BigQuery), NoSQL database storage (Cloud BigTable), data sync tools (Cloud Pub/Sub and Cloud Data Transfer), machine learning and AI-based deep analytics (ML Engine), dashboard facilities (Data Studio), data-science workshop (Cloud Datalab), etc. Specific training is required from newbie users while those ones who are already on Google Cloud consider the system simple and user-friendly.  

Oracle Enterprise Data Management

The very name of this system reveals what it is about. The system’s features enable organizations to consolidate the variety of enterprise data in quite an authoritative manner. Deployments for Windows, UNIX, and Linux are available along with cloud services.  

The system simplifies repetitive business processes and cross-functional workflows. It supports many programming languages and different databases to make the migration, visualization, and governance of data easier. Advanced search and flexible browsing facilitate access and validation of data as well. This is a purely corporate data management solution that requires quite intense training. 

Informatica PowerCenter

“Deploy projects in days, not months” as one of the system’s slogans encourages. The system is about the automation of data processing across the enterprise. It is ranked as customers’ choice 2021 by Gartner. The platform can transform raw fragmented data into ready-to-use datasets for both B2B data exchange and internal data management. 

The scalability and flexibility inherent in PowerCenter allow meeting the complexity and increased volume of data when a business keeps growing. Advanced data integration with multiple cloud services and on-premise systems makes the platform a universal data management tool for data-intensive business models. Real-time data analytics facilitates validation and quality control of multi-sourced datasets. 

Steps to turn a company into a data-driven enterprise 

The very availability of some advanced data management software does not mean that a company becomes a data-driven enterprise automatically. There should be a clear algorithm of how to use data management tools under a proper goal-setting. The following steps allow grasping the sequence of actions worth taking to utilize the full functionality of a data management system over the process of digital transformation. 

  1. Rearranging the existing data management to implement a new role model in which segregation of duties takes place. That is to result in better quality control of data, cross-checking of data between system processes, and detection of unreliable info. 
  2. Setting up data collection. That leads to establishing a unified data management paradigm without complicating the data validation to keep business processes going unchanged. 
  3. Arranging data integration. That means automation of processes that allow delivering the right data to the right destinations at the right time. 
  4. Implementing fully-fledged quality control of data. That implies determining quality control parameters along with developing methodologies of using automated systems. 
  5. Applying data management tools to the verification, deduplication, and rectification of all collected data.  

The above-mentioned steps constitute the general algorithm with which efficient data management workflows have a chance to appear within an organization. Of course, each of those steps should be divided into smaller sub-steps to settle all data management issues one by one. However, novice users of any data management software can unlikely meet the challenge just offhand. You will need a certain practical experience.  

Guaranteed software project success with a free 30-minute strategy session!

Get started

How DICEUS can assist in making your data management easier 

Having rich expertise in many IT domains DICEUS can start from a brief but thorough audit of the existing data management system at your organization. After that, a clear insight on the most appropriate data management software in your case can appear. No matter which platform you choose for data management since DICEUS can provide the full scope of software support and maintenance services according to your business needs. 

Our professional designers of software architecture can suggest what options should constitute the best system configuration for your data management solution. According to their suggestions, our engineers and developers can help your IT department set up and preconfigure the selected data management software without spending redundant time on manuals and tutorials. 

DICEUS can assign a dedicated team of professionals to train your staff in acquiring practical skills on how to use the full functionality of the data management platform you choose. The slightest nuances and peculiar features of any from the top data management software can quickly become familiar for your staff with our assistance.  

Besides, DICEUS can provide the full range of data migration and system integration services to make your data management system work like a custom solution.  

Contact us to make data management software start adding extra value to your business right away.