How do I select a data management solution for my business?
A continuous data growth has become the number one challenge for data management. To tackle these challenges, organizations should look for tools and platforms they can trust and which will allow them to keep data secure while not disrupting their business flow and not weighing too much on their budget.
To select a suitable data management solution for your business, you need to think about a variety of factors. We’ve talked to several industry professionals to get their insight on the topic.
Tuukka Ahoniemi, CEO, Tuxera
Four criteria should be critically assessed.
Software. The differentiation for data management has shifted from hardware to software in the past years: everything is nowadays software defined. Great data management software can make magic out from even older legacy hardware. This allows cost savings on re-using old hardware with modern solutions.
Performance. The amount of data that modern businesses need to handle has grown significantly. In addition, the data needs to be either moved around or processed locally in real-time without delays. Especially with AI and machine learning applications it is crucial that the data management does not become a bottleneck for the process. Higher performance data management results in more data output and improved production.
Reliability. It is unrealistic to expect that a system would never fail; both hardware and software can fail and instead of denying this, the systems must be designed to be fault tolerant. Also, don’t be fooled by “close enough” percentages: continuous availability means 100%. A data management system that guarantees 99.9% uptime will have 0.1% downtime which in large scale systems can be a significant number of issues. Lost user data or unsaved work can be irreplaceable and unacceptable.
Security. Finally, this goes without saying. One can’t afford to ignore this.
Stijn “Stan” Christiaens, CTO, Collibra
Identify a business case: It is critical that IT and security leaders prioritize investments in solutions that can deliver clear and specific business value by addressing blockers and enabling other teams within the organization. Having a specific business case in mind will set leaders up for demonstrable success. If your organization has a Chief Data Officer, be sure to connect with them as they may have immediate business opportunities in need for technology support.
Prioritize interoperability: Data management solutions must break down, rather than exacerbate, siloed work and data. Therefore, leaders should identify solutions that play nice with the rest of the organization, including both the internal technology landscape and the working patterns of teammates.
Invest for growth: Successful data management investments will solve today’s challenges while also being able to scale and grow to support future challenges. Leaders should look for solutions that are proven to scale and help customers address multiple use cases and priorities over time. The goal is to start small, but eventually go big!
Join a strong community: Data management is ever-changing, and data professionals benefit from sharing lessons learned. IT and security professionals should look for data solutions that have a strong community of active users, as these community participants can be a crucial resource for achieving adoption and success.
Mark Delsman, VP of Product and Engineering, FalconStor
Let’s face it, data management used to be pretty simple: systems were all on-premise, data was transitory (meaning the data were willfully deleted after a set period) and hackers weren’t around every corner. Today, it feels as though the opposite is true: data is everywhere (on-premise, at the edge, in the cloud), and is retained indefinitely, making it vulnerable in more locations and over a longer time period to errors and a growing pool of attackers.
So when selecting a data management vendor, consider the following questions:
- Does the solution play well across on-prem, cloud and edge, since data often moves over time?
- Can the solution give me visibility across all of them so that my team knows where it all resides?
- Can the vendors support all different forms of media for long-term preservation?
- Can the solution automate secure movement to the right medium or location to lower risk and lower cost?
- Can the solution detect and report on the security and integrity of the data automatically, and without the need to remount or move the data, which can increase costs in the form of people, time, and, in the cloud, egress fees?
Today’s enterprise should feel confident that the data management solution can provide the visibility and granular data security capabilities to support long-term data retention at scale.
Aaron Kalb, Chief Data & Analytics Officer, Alation
With the growing demand for data management tools, many offerings have emerged, but not all are created equal.
To choose the right system for your business, look for the following five critical components:
- Intelligence – Every organization has too much data and not enough people; leverage AI & ML to make data management manageable.
- Collaboration – With effective collaboration, each contributor works toward a common goal, building off of the work of others, and opening the door for greater innovation, and deeper insights.
- Guided navigation – Guided navigation helps data consumers find the right data and use it properly. Rather than giving data consumers a static repository (like an old paper atlas), provide them with turn-by-turn directions to their data destination.
- Active data governance – The best data management systems learn from user activity and put policies into action in users’ workflows—an approach to data governance that actually works.
- Broad, deep connectivity – To be able to effectively guide analytics work, spur collaboration, and encourage active data governance, data management software must connect to many different data sources, and enrich basic technical metadata with insights and recommendations.
Deepak Mohan, EVP, Products Organization, Veritas Technologies
Today’s digital landscape is extremely fast paced. Now more than ever, companies need a data management solution that can properly store, manage and secure all of their data in order to enable business resiliency.
Here are a few key features to look for:
Cloud-native data protection and availability: As more applications migrate to the cloud, solutions need to offer the same level of data protection and application availability in the cloud as on-premise. Any type of downtime costs the business money.
Backup and recovery: When it comes to backup and recovery solutions, multiple products increase cost, complexity and risk. The ideal solution will be able to store and protect all of your data no matter where it lives. Look for a solution that can automate backup copies on a regular basis – as well as quickly recover data after a significant data loss experience such as a natural disaster or ransomware attack.
Insights and analysis: To make intelligent decisions about your data, look for solutions that offer insights with a single pane of glass. You can reduce both storage and legal costs, while ensuring compliance with regulations and data privacy laws.
Marek Ovčáček, VP of Platform Strategy, Ataccama
Depending on your data landscape, when looking for a data management solution, you might want to consider a few different things.
First, I recommend getting a general idea about the sources and types of data you want to manage now and in the future. Obviously, you want to select a data management tool that can support these data sources.
Second, you want to make sure that the data management tool has proper integration options that can seamlessly integrate with your processing landscape. In the current market, this usually means you want to invest in solutions that support hybrid and edge integration options.
Third, I recommend that you look at data management solutions that have built-in automation and quality control, such as automated metadata capture and classification, data quality, and anomaly detection. When a tool uses AI/ML for automation, be sure that the tool uses an explainable and user feedback-trained solution, as opposed to a black box approach.
Lastly, compliance with regulatory requirements is something that any successful business needs to deal with sooner or later. For that, you might want to consider solutions that not only catalog policies based on regulatory requirements, but also control and enforce them.
Krishna Subramanian, COO, Komprise
Data growth is exploding, and enterprise IT organizations are moving more data storage to the cloud to manage costs. This underscores the importance of a data management solution that works across data centers and clouds to track where your corporate data sits and manage secure access to the data.
Enterprises can no longer rely on storage solutions alone to provide data management because that leads to a siloed approach and creates significant security risk when data moves across cloud or storage silos.
Storage-agnostic data management solutions provide visibility into all your enterprise data, particularly unstructured data, across vendor storage and cloud silos. This helps you understand how much data you have, who is using it, and how fast its growing.
Analytics-driven data management software also helps you move the right data to the right place at the right time with full preservation of security and access control across vendor silos. This is key to not only managing data growth and costs, but to also maintain data security.
Look for data management solutions that deliver visibility into unstructured data across vendor and cloud silos, move data based on your operational policies, and provide reports on access control integrity (eg MD5 checksums).
Heath Thompson, President and General Manager, Information and Systems Management, Quest Software
Businesses should look for a data management solution that takes a holistic approach, breaking down the silos between IT, security, and the business teams utilizing the data.
A recent study shows that 84% of organizations believe their data represents the best opportunity for gaining a competitive advantage during the next 12-24 months. And holistic data management is key to realizing this competitive advantage and empowering your organization.
Your data management journey should begin with an assessment and cataloging of your data, understanding your data, and the applications, systems and infrastructure that provides and supports the data. It’s important to establish a single source of the truth for the data needs of your business.
Modern data management also needs to consider not simply managing volumes of data, but rather focus on providing continuously available, high-fidelity data at the points of need throughout the business. Managing the operations of data pipelines is essential, with the ability to monitor, meet SLAs, and optimize both performance and cost.
Your data management solution should support a flexible set of policies around data access, ensuring the security and privacy of the business’ data throughout its lifecycle. Lastly, your data management solution needs to support the many domains where data reside: in multiple clouds and SaaS applications, on premise in heritage applications, and most likely, in a hybrid of all the above.