Skip to main content

How to Move to Modern Data Management


The world of data management is changing. In the age of big data, businesses must cope with an increasing amount of data that’s coming from a growing number of applications. There’s enormous value to be gained from technologies such as AI and machine learning, but you have to have the data platform to support them. What can you do to transform your business’s existing information management systems into a modern data management platform? Read on.

What is modern data management?


There’s been an enormous shift in data management technologies and practices over the past several years. Older data architectures, such as on-premises relational databases and data warehousing, can no longer keep up with growing volumes of data. Data latency is no longer acceptable when businesses are looking for real-time data to make immediate business decisions.


A modern data management platform is scalable, flexible, and based on open standards. It can handle vast quantities of data in numerous formats, such as streaming data from IoT devices in near-real time.


We may need to implement new technologies to create a modern data management platform, but we also need to consider how these changes impact our people. Roles and skills that were essential for on-premises data environments may no longer be needed in cloud environments. Tasks that used to require IT intervention can now be performed by business users. We need to consider how to build teams that can help us move forward and how we can help data professionals update their skills.


What are the characteristics of modern data management?


A modern data management has the following features and characteristics.


Cloud-native. Given the growing scale and complexity of data today, companies must take advantage of the speed, scale, performance, and economics of the cloud to support their modern data management platform. It’s no longer cost-effective to continue adding physical infrastructure to support growing data volumes. The cloud provides the flexibility and scalability to support today’s massive data volumes.


Robust data integration. Data integration is an essential characteristic when we talk about the modern data management platform. Without a single source of truth for your data, it’s hard to gain value from it. So we must be able to consolidate all of the data from all of the different systems that run our organizations. When all of this data is integrated, it can become a source of valuable business insight. When we can see all of the data from an organization in a single, unified view, we can use it to make better business decisions.


Data virtualization. The issue of data integration leads us to data virtualization. When it is impractical or cost-prohibitive to physically consolidate all of the data from your organization in a single location, data virtualization can be used to virtually consolidate it. A data virtualization approach gives users a near-real-time, consolidated view of data via a single interface, even though the data remains in separate source systems.


Security features. A modern data management system needs to have appropriate security measures in place. Data breaches are damaging in multiple ways, and the bigger the breach, the more damaging it is. There must be security controls in place to prevent data breaches or data loss. In addition, many data assets need to have role-based access controls in place so organizations are can manage who can access what data.


Proper data governance. Some people confuse data governance with data management. Maybe because data governance is an essential component of the modern data management system. An effective data governance strategy is essential to maintain regulatory compliance, minimize risks, improve data security, and create accountability for data throughout the organization. Data governance policies can also be used to create and enforce standards for data quality. If we’re going to rely on our data to make decisions about our businesses, we have to know that we can trust that data. You can’t make good decisions using bad data.


Flexible and extensible. Right now, everyone’s talking about advanced analytics such as machine learning and AI. But there’s always going to be the next development, the next technology. A modern data management platform is based on open standards and built on a loosely coupled architecture, so new functionality can be added quickly and easily.


Delivers value to users. The ultimate goal of any data platform is to make it faster and easier for users to gain access to the business data they need to do their jobs. When your users have easy data access, your data platform is doing its job.


How to move to modern data management


Assess your existing data architecture. The first step is to get a clear picture of your existing data architecture. Where are you storing data? How many systems do you have that generate data? Is your data currently integrated? What do your users need in terms of access to data? What does the business need?


Determine an ideal future state. You want a solution that is scalable and flexible enough to meet your needs for the next several years. Because of the scalability of the cloud, many organizations are using cloud data warehouses as the basis of their modern data platform. Remember that you will also need tools to load and transform data, such as an ETL tool.


Build a team. As organizations cope with more data than ever before, data teams need to adapt and change. Assess the skills within your existing data organization and identify any gaps. You may decide to train existing staff on newer data technologies.


Want to get started with modern data management?


Matillion products can help organizations with modern data management. They provide a complete data integration and transformation solution that is purpose-built for the cloud and cloud data warehouses. Matillion can also help as you build a modern data team.


Matillion Data Loader makes it simple to replicate your data into a cloud data warehouse, allowing you to create a single source of truth for your data. Built as a SaaS-based data integration tool, Matillion Data Loader includes a number of integrations and gives you a 360-degree view of all your data sources.


Looking to get more value out of your data? Matillion ETL software allows you to transform your data into insights and decisions for your business. Request a demo and learn more about the transformative power of Matillion ETL.