Data management tools: choosing the right one
Managing data is a foundational part of any business nowadays but it isn’t easy and some of the pitfalls which commonly emerge are storage problems, duplicated or inaccurate data across systems, or confusion about the location, sharing and compliance of data. So, whether it’s a retailer, supplier or manufacturer, effective use of data management tools has to be a given to be competitive in a crowded digital marketplace.
Fortunately, there’s an array of data management tools available to cover all areas of data management, the majority of which are cloud-based applications with a subscription-based payment system:
- Updates are usually inclusive
- It’s easy to scale data management tools as the business expands
- These tools are cheaper per user than buying and installing a software suite on your servers (which your IT department has to administer and maintain)
- Most tools are equipped with APIs, so easy to integrate with existing systems
- using artificial intelligence, they save time with automation for high-frequency functions
What is a data management tool?
Data management tools deliver the storage, synchronisation, analysis, and dissemination of:
- Product information
- Customer databases
- Administrative and financial resources
- Multimedia files and other data
They save you time and costs and eliminate redundancies and inaccuracies. You can easily share data with commercial partners, warehouse teams, sales reps, or distributors as well as syndicating processed information to sales channels.
There is no single data management tool which satisfies all your needs, although when focusing on product management tools, such as a PIM, you can find software suites with several tools built in. These offer centralised and harmonised data management, and as an aid to strategic decision-making.
The key features of effective data management tools
Ideally, tools offer the following advantages.
- infinite volume: However large your database becomes, master data management tools should be able to manage infinite quantities of data and fields.
- collaboration: Any user with access permission can use the data management tools, anywhere, anyhow and any time. The centralised functionality of data management tools make them highly suited to distributed organisations deploying remote working and international teams.
- eradication of bad data. Up to now, eliminating errors manually has been difficult and haphazard, but automated functions can now practically guarantee 100% accuracy, especially important in a product management tool.
- security, efficiency, and privacy: these are more robust and less prone to breaches, with backup generation, change history and data recovery options providing a safety net.
- optimised storage: whether it’s Excel files, images in multiple formats, PDFs or Word docs with translations, product management tools save on space, precisely because they are cloud-based.
- Role-based data access: you save time by being able to access the data you need at all times. Additionally, you can rely on those data, and share them in any format with third parties or across digital channels.
Master data management tools can also centralise data using different criteria, such criteria will influence the type of model you need – relational, hierarchical (in tree format) or networked. for instance, in product information management, relational databases are suitable for linking information fields which are mutually dependent, such as colour, size, and model.
Testing data management tools
Data management tools incorporate features aimed at the enterprise-level business profile (large), so can be costly and complex to implement, requiring specialist third-party input and user training. Testing data management tools is essential, as is time for staff to familiarise themselves with and adapt to the tool(s), be they master data mangement tools or product management tools.
Another crucial element is to establish a watertight data governance framework for the appropriate user permissions and access rights for clarity of role, data security, and efficiency.
Types of product management tools
Master Data Management (MDM)
Master Data Management tools centrally manage multi-domain, master data for an organisation at various levels – business, employees, customers, accounts, operations, regulations and more. It consolidates this comprehensive data volume into a single source, which can then provide integrated data applications to any business function. Typically, a cloud-based MDM platform includes:
- Data cleansing, standardisation, and quality assurance
- Keymapping (linking unique identifiers from multiple systems)
- Transaction Control (managing various transactions occurring across a relational database system)
- Multi-Domain support (customer, logistics, marketing, product, etc)
- Information distribution
- Global synchronisation
Its broad function is to ensure the master version of each data point is accurate, complete, and consistent across the organisation, its enterprise systems, and its partners.
Product Information Management (PIM)
A Product Information Management solution (PIM) is the go-to product management tool for manufacturers, distributors and retailers who need a central hub for all product-related data. Leveraging automation, it allows users to onboard, manage, enrich and syndicate customer-facing product information across all sales channels, catalogs, business partners and end to end supply chain.
Digital Asset management (DAM)
With the boom in eCommerce and development of the digital shelf, Digital Asset Management (DAM) software is increasingly important. It centralises media assets like images, graphics, documents, videos, 3-D models, and other enriched media. Modern PIM solutions frequently contain a built in DAM, given the increasing need for comprehensive digital experience management. A DAM integrates, consolidates, and manages any type and amount of digital assets.
Data Modelling tools
Embedded as part of master data management tools and product management tools, data modelling eases adaptation of incoming data to the required format for storage. Data modelling tools can generate conceptual models to establish the rules necessary for consistency and quality. The data ‘model’ refers to any given data, their characteristics, and their relationships with other data. For product-centric businesses, MDM organises SKUs to make them easily accessible throughout their life cycle.
Digital shelf analytics tools
Digital Shelf Analytics tools are used extensively to offer insights into performance on the market – they typically report on metrics like SEO and content quality and completeness. Sales and marketing teams commonly use these metrics to respond to rapid market changes or mounting campaigns.
Other data management tools
When a new system such as a PIM solution is implemented, it impacts on both operations and strategy. Embedded tools with highly specific functions include:
- data quality analysis
- data cleansing
- metadata management
- data architecture
Selling products in the twenty-first century deploys a range of business operations to optimise processes and create competitive personalised and omnichannel customer experiences. Data management tools like MDM, or product management tools like a PIM and, with automated functionalities built in are essential as the basis for these operations, as they:
- Provide a single, centralised data source
- Are a guarantee of high-quality data
- Can be integrated with other platforms to onboard, store, extract, enrich and syndicate data for optimised content for websites, marketplaces, apps, supply chain, warehousing and much more.
At Start with Data, we have the know-how to guide, advise and support you in your journey towards digital excellence. Contact us for a more in-depth conversation about how we can help you to get your data into tip-top condition and thrive, both on and offline.