Master Data Management - ChainSys Blog

Data Governance Vs Data Management: What’s the Difference?

by | | Data Integration, Data Migration, dataZap, Master Data Management

Data is information such as numbers and facts that are used to analyze and contribute to decision-making. It is considered to be a precious asset for organizations today, but it can also be a dangerous asset when it is managed in the wrong way. The way of managing and governing data may lead to a huge success or massive breakdown for the organization. Data is like a child, and its future solely depends on how it is nurtured. Data Governance and Data Management act as parental figures to data. In this blog, we will discuss in detail the difference between data governance and data management, and how dataZen, a part of the smart data platform offered by ChainSys helps to leverage data to its fullest potential.

Understanding Data Governance

Data governance refers to the set of policies, procedures, and standards that guide the management of data assets. It manages the actions and processes people must follow. It also monitors the creation of data dictionaries to make sure everyone has an understanding of the data and ensures that various departments across the organization use the data in a consistent way.

Policies and Standards: Establishing guidelines for data usage, security, and compliance.
Data Stewardship: Assigning roles and responsibilities for data oversight.
Data Quality Management: ensuring the reliability, consistency, and accuracy of data.
Compliance and Security: Ensuring data practices comply with legal and regulatory requirements.
Data Catalog: Providing a comprehensive inventory of data assets and their metadata.

Why is Data Governance Necessary?

Many organizations today are expanding quickly, and every day, systems perform a huge number of transactions and generate enormous volumes of new data. There is always a possibility of physically or digitally entering wrong or duplicate data, which can result in a big data failure while decision-making. With the use of dataZen for data governance we can avoid these situations because its goal is to ensure that data is accurate, complete, and secure, and also verify whether it meets the needs of the organization. dataZen takes control of the overall management of data assets within an organization by defining the rules and regulations around data access, usage, and sharing.

Understanding Data Management

Data management refers to the processes and tools that are used to acquire, store, organize, maintain, and analyze data. Data Management ensures that the data is accurate and consistent, and available for use when needed. It also ensures that an organization is using the most updated form of data available.

Data Integration: Combining data from different sources into a unified view.
Data Storage: Efficiently storing data in databases, data warehouses, or data lakes.
Data Security: Protecting data from unauthorized access and breaches.
Data Archiving: Preserving data for long-term storage and future reference.
Data Migration: Moving data between systems, applications, or storage environments.

Why is Data Management Necessary?

To develop effective business strategies every organization completely depends on data. An organization’s progress is significantly influenced by relevant, accurate, and usable data. It can become useless if not well managed. But dataZen for data management can guarantee the accuracy, availability, and accessibility of data to be processed and analyzed, therefore helping in making better-educated business decisions and gaining an in-depth understanding of customer behavior, trends, and patterns. To get the most out of the data they have access to, it has become crucial for enterprises to adopt data management. The benefits of dataZen for data management are listed below

The Relationship Between Data Governance and Data Management

To get the most useful business insights from data, data governance, and data management must be used in tandem. Without data governance, data management is like a building without an architectural plan. Data governance, on the other hand, is just paperwork without management.

The difference between data management and data governance is

Data governance is the overall management of data assets within an organization whereas data management refers to the operational activities involved in managing data.
Data governance involves defining policies, procedures, and standards for how data is collected, stored, processed, and used while data management includes the processes and tools used to collect, store, process, and analyze data
Data governance ensures that data is consistent, reliable, and trustworthy while data management ensures that data is available and usable for the people who need it
Data governance verifies the data used is consistent and used across the organization whereas data management verifies that the data is available in the right format, at the right time, and in the right place.
Data governance includes data dictionaries and data catalogs whereas data management is more concerned with data storage, processing, and exploration.

dataZen is a master data management tool that enhances data quality and tightens security within the enterprise. It has over 7000+ master data templates, for over 200+ endpoints.
Proper “System of Record” for master data, provides a Centralized data hub for consolidated reporting and querying of master data.
It has preconfigured workflows supporting data governance and approval processes, and does data encryption and masking to keep data safe while at rest and in motion. This creates a single source of truth.

In conclusion, Data governance and data management are two distinct aspects of data management. data governance is focused on defining policies and establishing a framework for managing data, data management is focused on the day-to-day operational activities involved in managing data.

Even though both have different characteristics, both play a vital role in the effective management of organizational data, and they complement each other in ensuring that data is managed effectively throughout its lifecycle. With help of dataZen, you can fix fundamental issues with master data management such as duplicates, fragmentation, and inconsistency across systems, and also establishes master data governance rules to define a common data model, and master / transactional data creation using a workflow which creates a huge impact for a data.

Data Management Services Help Your Business

by | | Data Integration, Data Migration, dataZap, dataZen, dataZense, Master Data Management

How Data Management Services Can Help Your Business?

To run an organization successfully, every business needs data. Massive amounts of data of various kinds are being gathered and stored by businesses, but managing and analyzing this data could be difficult. In this case, data management services can be useful and also considered to be a crucial component of corporate operations in the current digital era. We’ll explore more about what data management services are and ChainSys, a data management firm, offers a variety of data management services that help your business in this blog.

What are data management services?

Data management services refer to a collection of procedures and tools for gathering, archiving, organizing, securing, and maintaining data across the course of its lifecycle. It includes a broad variety of operations, such as data integration, data governance, data migration, data quality management, data analytics, data security, and data storage.

Let’s take a closer look at various data management services:

Data Integration:

The process of merging data from various sources into a single, unified view is known as data integration. dataZap, Chainsys’s integration platform helps you integrate and transform data from any source. No coding is required and high volume integrations of up to 1 million records can be done in an hour. It also keeps data clean by validating & cleansing during data integration.

Data Governance:

Data governance refers to the set of policies, procedures, and standards that guide the management of data assets. It manages the actions and processes people must follow. With dataZen it is an easy-to-build workflow with data governance tools and it monitors the creation of data dictionaries to make sure everyone has an understanding of the data, to identify, it collaborates with various departments across the organization to confirm that the data is used consistently across the organization.

Data Migration:

Transferring existing historical data to new storagee, a system, or a file format is known as data migration. While the process may sound quite simple, it requires a change in storage, a database, or an application, but ChainSys approaches complex data migration to various ERP and Enterprise Application needs with simplicity and robustness with its ready-to-use 7000+ Data Adapters for Data Extraction, Data Loading, and Data Mappings from Source to target applications.

Data Quality Management:

Data quality management (DQM), a business strategy, aims to enhance the data quality metrics that are most important to an enterprise company, by bringing together the necessary people, procedures, and technologies. ChainSys’s cloud-based dataZen data quality management platform enables businesses to identify inconsistent and erroneous data across their applications and provides you with data cleansing tools as well as the ability to de-duplicate data.

Data Analytics:

Data analytics refers to a collection of quantitative and qualitative methods for extracting insights from data. With dataZense a holistic data and analytics platform provides rapid results by following the most efficient processes to ensure governance and quality to bring forth a single source of truth for information at all times, thus driving sustainable decision-making across businesses.

Data Security:

Data security is the process of defending your information against unauthorized access or usage that can expose, delete, or corrupt that information. Using dataZense for Data Security, you can avoid internal and external data breaches and have simple sensitive data management by providing comprehensive data security management, data masking, and data scrambling solutions for many applications.

In what ways the above data management services can benefit your business?

To conclude, data management services can help businesses in many ways, from improving decision-making to reducing costs and gaining a competitive advantage. Whether it’s a small business or a large enterprise struggling to manage data, ChainSys smart data platform would be a great investment as it helps in maximizing the value of data.

What Is Master Data Management and Why Is It Important?

by | | dataZen, Master Data Management

Working with data is unavoidable for companies that want to stay relevant. However, just “working with data” isn’t always enough to cause you to stand out from the pack. To set yourself apart, you need to work with data more efficiently and effectively than your competitors. That’s where master data management comes in. But what is master data management, and why is it important?

You’ve come to the right place. Read on to discover what you need to know about master data management.

Master Data Management: Explained

To understand the management part of master data, the first step is understanding master data. When we break it down to its simplest definition, master data refers to the most vital instances of data in your enterprise—all of the information that’s required to conduct business.

Of course, this can be further divided into a few different domains. For instance, your customers, products, and locations are all key elements of master data. Without any one of those elements, your company could not survive. You should also consider a subset of “other” factors, like warranties and contracts. All these unique elements comprise your master data.

Master data management, then, refers to how your business handles all that information. Now, things may get a bit more confusing. Master data management technology, often called MDM, allows you to perform tasks with data management in mind. Master data management as a discipline is more conceptual—it gives you principles that will help you govern your data successfully.

Reduced Workload

The collection and maintenance of master data is a full-time job—one that you should leave to a dedicated master data management system. Without one, you’re expecting every department to spend time managing their own data alongside their regular job functions.

As soon as you remove data management from the workload, all your departments will find it easier to complete their work on time (or even early). A master data management system allows you to collect each piece of data simultaneously rather than having each department collect and utilize the data separately.

Over time, this makes your business quicker and more efficient, which saves you money while getting the reports you need on time.

Higher Data Quality

When separate departments are responsible for maintaining their data, you’re bound to run into snags along the way. Without a way to manage master data, departments will grow away from each other rather than together, leading to problems with collaboration that only increase as you go.

Master data management allows everyone to access a single source of data, which means your information will not dilute as time goes on.

Avoids Data Duplication

One aspect of data quality that is often overlooked is duplicate data. When you don’t have a system that can look for and detect duplicate data, you may find yourself with information that gums up the works. With a decentralized data application, you’re more likely to run into redundancy that can take up your time and cause errors throughout the process.

Duplicate data becomes a significant hurdle when you acquire information from customers. Slight changes in your questionnaires over the years may cause customers to enter their information multiple times in slightly different ways. For instance, you may have records that refer to a customer living at 1340 Delta Avenue and another record that lists them at 1340 Delta.

You don’t need both these instances, and it may cause a less intelligent program to assume you have one more customer than you do. When this issue occurs across hundreds or thousands of customers, you’re left with analytics that doesn’t accurately reflect your customer base.

With an MDM solution, you won’t need to worry about duplicate data. Your MDM will scour through data to find repeat instances and remove them, increasing your efficiency.

Reduced Time-to-Market

Setting up new systems is always a headache, right? It doesn’t need to be with a dedicated MDM. Connecting a new system to your primary MDM system instantly populates the new application with all the data it needs to hit the ground running.

Upgraded Decision Making

When all your data is in one place, your teams can make decisions with a clearer picture. Without a master data management system, you can think of this process like putting together a puzzle without the box—you may have all the pieces, but you don’t know the picture you’re trying to create!

As new data comes in, it instantly updates the information across your company. This leads every team to make decisions with all the latest information they need to propel them toward success.

Compliance and Governance

Regarding benefits, “compliance and governance” may not be the most attractive words, but they are some of the most essential words should you want your business to stay strong for years to come. While it may sound more appealing to increase efficiency and reduce your workload (which MDM can also do), you can’t maintain a company without staying in compliance and structuring your systems with governance.

This structure allows you to restrict access to data, giving your employees the information they need to do their jobs effectively while preventing them from accessing data they shouldn’t. All interactions with data are also cataloged, which means it’s easy to trace problems back to their source so you can correct them.

Reduced Security Risk

Extrapolating on this further, MDM tools also assist you in tightening your security. Breaches are extremely serious; if they happen, you can quickly see where the problem began so you can address it.

In all, a business equipped with the right master data management tools stands to work more efficiently and safely than other companies in the game.

Now that you know what master data management is and why it’s important, start the next chapter of your business’s story and begin working in an MDM system. You won’t believe how adding an MDM system to your business pipeline can completely transform how you work!

A Fortune 500 Pharma Company’s successful journey on Master Data Deduplication

by | | dataZen, Master Data Management

With being one of the data-dominated industries, the pharma industry comes across various data management challenges. The regulatory compliance standards, document submissions, changes in SOP processes, mass data inputs in both domains of vendor details and patient details leads to duplicates & incorrect data entries, and complexities in financial architecture in regards to receipts, bill payments, and other purchase information.

For the next pandemic years, having a single source of truth or consolidated Master Data for the whole pharmaceutical sector is becoming increasingly important

How ChainSys streamline a Pharma company’s Master Data?

ChainSys’ dataZen provides a single source of truth to materials, customers, suppliers, formula, receipt, bills of material, pricing, equipment, and real-time data at scale to accelerate research and development and also to improve their time-to-market.

dataZen’s Master Data Management principles

A Single Platform for Data Quality Management (DQM), Data Governance & Master Data Management (MDM)
A multi-domain strategy ensures that nothing is overlooked
Configurable and agile, with very little or no programming
Built-in Data Quality, Profiling, Deduplication, Consolidation, and more
Easy to build workflows for Data Governance

How dataZen stimulates and reduces complexity with health care data?

Benefits

Centralized customer hub for transactions
Eliminated manual onboarding and application process
Avoiding the creation of duplicate multiple user accounts
Applied customized business rules to identify duplicates

Key takeaways

Clean single-source master data
Automated business validations within ERP
Easier dashboard integrations to help find duplicates
Rigorous business user process made seamlessly

ChainSys’ dataZen solution offers a flexible and minimalist business workflow, qualitatively distinguished data, a centralized customer hub for simpler form submissions, and an automated business rules engine to eliminate manual procedures.

Learn how dataZen benefited a fortune 500 pharmaceutical firm!

Download the case study here