Modern society is powered by data. Our day-to-day has become increasingly digitalized, representing a valuable source of data for businesses across the globe. However, due to poor data management strategies, many organizations face challenges in maximizing their data power and run into roadblocks that prevent significant benefits.Â
Without robust data strategies, organizations can not meet the growing business demands of today’s ecosystem and fail to deliver trusted and secure information – leading to competitive threats, poor delivery of innovative products and services, and decreased customer satisfaction.
For this reason, organizations must drive constant innovation in data management architectures to power their massive, rapidly growing, and evolving datasets to deliver more intelligent services and achieve increased business growth.Â
Let’s dive into the key steps for ensuring future-proofed data management strategies.
Addressing the challenges
Before discussing potential solutions, we must address the main challenges faced by organizations today:Â
1. Outdated systems
Outdated database models can be an organization’s worst enemy and will rapidly limit digital transformation efforts as they’re unable to keep up with the speed of modern business growth. One example would be organizations leveraging legacy systems and outdated IT management solutions. Although some organizations keep them around because they still perform the functions they initially intended to, traditional models can be expensive as they cannot process large-scale data transactions and are highly prone to single-point failures (which will stop an entire system from working).Â
2. Poor data quality
As companies deal with an increasingly competitive market, accessing concurrent data and conducting real-time analytics is crucial. Lack of efficient database technology creates barriers to data access, resulting in data silos that limit leaders’ ability to make intelligent and informed decisions in real time. This is due to outdated systems that struggle to perform data analytics in real-time and can take up to days to complete proper data migration – hurting an organization’s overall agility.Â
3. Shortage of skills
Like in many other industries, one of the biggest problems companies face today is the skill shortage in the data and technology sector. The demand for data scientists has grown exponentially, and the current labor shortage creates a difficult situation for organizations looking to build advanced teams. To remain competitive in the current landscape, companies need to focus on investing in training talent while continuing to pursue building a solid team poised to handle their digital transformation goals.Â
4. Lack of clearly defined data governance policies
Data governance (DG) is a core component of a healthy data management strategy. By definition, DG is the process of managing the availability, usability, integrity, and security data within enterprise systems. Rules are set based on internal data standards and policies that help control data usage to ensure that data is consistent and trustworthy while avoiding misuse. Without effective policies, inconsistencies across organizations might not get resolved, which can complicate data integration efforts and create data integrity issues that affect the accuracy of business intelligence, enterprise reporting, and analytics applications.
See More: How Brands Can Keep Pace With Third-Party Data Changes
Embracing New Technology
To solve the challenges captured above, company leaders must adopt new and innovative processes that can withstand the evolving technology environment. To create flexible and reliable databases that will enable them to make faster, more intelligent business decisions, they must adopt modern strategies that solve the burdens at hand. Luckily, new hardware and software tools can quickly transform how data is managed.Â
Let’s dive into some of the key features that enterprises should look out for:Â
1. Cloud-native architecture
At a high level, cloud-native architecture means adapting to the many new possibilities offered by the cloud compared to traditional on-premises infrastructure. Most enterprises are becoming cloud-first, meaning they’re looking for cloud solutions when developing new processes. This change allows organizations to fully operate in public, private, or hybrid cloud environments while utilizing the cloud’s flexibility, scalability, and reliability. Â
2. Hybrid transactional and analytical processing (HTAP) technology
HTAP leverages the power of computing to bring online transaction processing (OLTP) and online analytical processing (OLAP) into one database. HTAP removes data silos and the need of ETL Opens a new window (which stands for extract, transform and load), a data integration process that combines data from multiple sources into a single, consistent data store and that is loaded into a data warehouse or other target system. Its architecture can quickly respond to transactional and analytical requests, ensuring that organizations always work with the most current data available – addressing specific business intelligence needs and solving previously mentioned agility issues.
3. High availability
When we talked about outdated database models, we emphasized that they are highly prone to single-point failures. High availability ensures database environments are consistently up and running, which prevents this issue – while providing increased uptime and enhanced performance. High availability guarantees that data within an application is always available and accessible, regardless of crashes, ensuring business continuity and more competitive business agility.
4. Open-source software
Open-source databases give the freedom to build new applications using existing database technologies. They are publicly accessible, enabling developers to utilize the source code to create a system that fits their unique requirements and business needs. This software development model provides enterprises and developers with multiple benefits, including flexibility, speed, transparency, and cost savings. Open-source also inspires innovation, as developers get to collaborate and contribute to multiple projects.  Â
Future-proofing Data Management Strategies
Without a doubt, data management is a high-power area of modern technology that continues to evolve. Leaders must embrace new technologies designed for long-term success to succeed in a world that demands greater agility from enterprises. For this reason, the time has come to face the fact that outdated databases, such as legacy systems, will only preclude leaders from achieving proper innovation and business growth at scale.Â
As enterprises embark on reassessment periods, adopting an out with the old, in with the new mentality will be crucial for those looking to thrive in the future landscape. Only by doing so will leaders be able to prepare their organizations to withstand growing business demands, make intelligent real-time decisions, and future-proof their overall business performance.
How do you think businesses can innovate data-management strategies to succeed in a cut-throat competitive market? Let us know on LinkedInOpens a new window , Facebook,Opens a new window and TwitterOpens a new window . We would love to hear from you!