Data management is the process of collecting, organizing, storing, maintaining, and utilizing information in an efficient and secure manner to support decision-making and achieve organizational goals. Effective data management is crucial for businesses to stay ahead of the competition in today’s fast-paced world. Modern practices have evolved to meet these demands, offering a range of benefits and features that legacy data management systems could not. This article will explore the critical aspects of modern data management and its advantages.
What characterizes “modern” data management and what are the benefits?
Data management has been around since there was data to be collected. Today, even though the amount of data has increased exponentially, some of the largest companies still rely on old technology and legacy systems that work “well enough” to manage their data. However, they are often slow and inefficient and can be more expensive to maintain than a more modern data management system. Modern data management encompasses the use of the newest technologies and solutions for managing data, and its goal should be to help a company more efficiently analyze, access, and share its data assets.
Data management strategies are considered modern when they are scalable, dependable, efficient, and effective. Specific benefits include:
- 24/7 Availability: Modern data management ensures data is available with minimal downtime. With the advent of cloud technology, availability has increased to levels as high as 99.99999 percent.
- Agility: Modern systems allow for rapid scaling, enabling businesses to respond quickly to changes in demand. This is particularly important when it comes to allocating space and resources.
- Cost-effectiveness: The shift to cloud-based solutions and more modern infrastructure has significantly reduced business costs. Expenses related to data centers, infrastructure, and staffing are dramatically lower with modern data management.
- Increased data volume: The rise of big data means that modern data management systems must be capable of handling vast quantities of information.
- Improved computing power using AI and ML: Modern technology facilitates increased computing power for the easier and faster integration of artificial intelligence (AI) and machine learning (ML) into data management systems, improving efficiency and enabling new insights.
- Self-service capabilities: Data lakes and other modern data management solutions provide a wide variety of users with self-service access to the information they need. This allows business users, data analysts, and data scientists to conduct analyses, generate reports, and easily make predictions.
- Real-time processing: Unlike legacy systems that rely on batch processing, modern data management can handle real-time data processing, enabling more accurate and timely insights.
When is it time to modernize your data management strategy?
Most companies decide to update or modernize their data management strategy when data and analytics processes that used to be efficient take longer due to larger volumes of data, and their outdated technology can no longer handle standard tasks. If they decide to maintain their legacy systems, scaling them can be costly, and even when moderate changes are made to existing systems, they may not operate as efficiently as modern systems would.
Another reason companies cite for upgrading their data management systems is to accommodate newer data file types that are now prevalent due to new data sources. With more modern management systems, analysts can combine data in various formats, like JSON files, XML files, relational databases, SQL data, and more, for faster processing and analysis. Using legacy systems, these file formats would typically be incompatible and require longer processing times to allow for conversions to usable formats.
What to look for in modern data management solutions
When evaluating new data management solutions, it’s essential to consider how processing speed and access factor into the success of your organization. Getting more accurate data faster facilitates better decision-making, but companies must decide if it’s worth the expense and effort to achieve this.
Industry also plays a vital role in a company’s modernization readiness and eligibility. For example, financial services companies and others in heavily regulated industries may be slower to modernize due to the constraints of regulatory compliance, which dictate how sensitive data is managed. Companies with this kind of information may be hesitant to store that data in a more accessible cloud-based platform because of security concerns. They typically opt for a hybrid solution that offers public cloud flexibility and private cloud security, where data is securely hosted on AWS or Azure platforms.
On the other hand, more agile industries like hospitality need to integrate data constantly coming in from various sources and locations, which makes them more apt to modernize their data management systems to accommodate their ever-evolving needs.
How to determine what data management strategy is appropriate for your organization
The choice of tools and platforms used for modernization depends on the company’s needs, budget, and resources. To recommend the right data management solution for an organization, it’s crucial for data solutions architects first to understand the company’s goals and how data will be used to achieve those goals. Using this information, they can evaluate the existing technology stack and data infrastructure to determine where updates and changes can be made.
The next step is to develop a plan illustrating how modern data management systems and new technologies can help the organization achieve those goals in the agreed-upon time frame. Complete digital transformations and system modernizations typically take six to 12 months. The larger the company, the more data they have, and the longer the transformation may take, even with the help of expert data consultants.
The tools and platforms used often rely on a company’s individual needs and preferences. Cloud computing platforms like AWS and Azure offer comprehensive data management solutions that handle everything from storage to management and reporting, so selecting the best tool requires understanding the company’s unique requirements.
Best practices for maintaining modernized data management
Once the investment has been made in a digital transformation, companies must also invest time and money into maintaining the solutions and ensuring that they are kept up to date. Comprehensive cloud service providers like AWS or Azure are constantly improving their features, so talent must be equipped to manage and optimize their chosen solutions to maintain the benefits of their modernization and stay competitive in their industries.
For example, after a digital upgrade, having an owner and expert in any new technologies can help keep the full team updated. At one of our customer companies, there is a data manager who became a certified Snowflake architect manager to serve as their internal Snowflake expert after we completed the implementation. He monitors how the platform is evolving by taking periodic training courses and attending conferences to help his team and their data management processes stay on the cutting edge.
How Wavicle can modernize your data management systems
The evolution of data management involves understanding the differences between legacy and modern technologies and identifying the best tools and strategies for a company’s specific needs. Wavicle’s consultants have deep industry expertise and are well-versed in widely used platforms like AWS, Azure, and Google Cloud so that they can recommend the best tools for your company’s needs. By staying proactive and adapting to change, businesses can ensure they are taking advantage of the latest advancements in data management, ultimately improving their decision-making and overall performance.
If your organization’s data and analytics processes are slow and inefficient, it might be time to upgrade your data management systems. Contact us today to learn how our experts can help future-proof your data and analytics infrastructure.