7 Steps to Choose an Enterprise Data Management Service Provider

Unsurprisingly, executives recognize the significance of data literacy for success, yet only one-fourth of those on the front lines express trust in their data. While some short-term fixes are available, companies must perform due diligence to ensure secure and accurate information.
Did you know? According to a survey by HBR, 9 out of 10 business leaders view data literacy as critical for success. In order to keep sailing businesses in the projected direction, organizations should rely on authentic and reliable data to make informed decisions, thus, achieving the business goals seamlessly.

Industries such as healthcare, banking, education, and FMCGs handle gigabytes of data on a day-of-day basis through various sources. With the amount of data being collected each day, it can be challenging to put the effort in the right place. Fortunately, with an efficient enterprise data management strategy set in place for your business, businesses can utilize this data and gain insights to reach new heights.

Here is where onboarding a stellar data management consultant can be handy! This blog will take you through the nitty-gritty of choosing an apt enterprise data management consultant for businesses to thrive efficiently in the data world.

STEP 1 – Hear out the Enterprise Data Management Service Provider’s Strategy

Formulating an effective Enterprise Data Management strategy from the top-down level enables the identification of which data management components and capabilities are essential for meeting business objectives. Furthermore, it should be established considering how close the current state of each applicable capability is to the desired future state.

An analysis based on an evaluation model that assesses data management maturity is an ideal starting point in developing an enterprise data management strategy and its roadmap. If the outsourcing organization analyzes the problem statement and puts forth a comprehensive data management strategy considering the future goals, then businesses can take it forward to the next phase.

(Add a gated content link with CTA)

Step 2: Does the Enterprise Data Management Service Provider have a competent ETL Process?

From extracting data from different sources to transforming it into a cleansed file for easy data visualization, the ELT process is significant in collecting the businesses’ raw data and uploading it to a data warehouse.

Since the outbreak of the pandemic, businesses such as healthcare and finance are likely to deal with a massive amount of data stored in different systems. ELT provides a great way to control and access all these records by offering the ability to load both unrefined and clean data for further analysis. Hence opt for service providers whose data management practice encompasses effective ELT processes and whose ability to utilize cloud-based data warehousing and advanced processing tools such as Hadoop is more efficient; thus, managing extensive amounts of information proficiently.

Read More – Data Analytics in Banking and Finance Sector

Step 3 – Can the Provider Manage Different Data Formats?

One of the most complex parts of enterprise data management is collecting data from different systems and putting it together in one place for data wrangling. While some systems provide data in a structured format, other systems provide data in an unstructured or semi-structured format. Structured data (each has sortable rows and columns) can be easily managed as it fits easily into a data warehouse with existing schemas available onto it. Suppose your business comprises systems that provide both structured and unstructured data such as pdf and videos, in that case, you might require an enterprise data management service provider with expertise in handling structured, unstructured, and semi-structured data.

• Some of the tools required to handle unstructured data are MongoDB, Azure, and Amazon DynamoDB.

• Irrespective of the type of data, it is essential to have the right solution to manage it. For instance, organizations handling a great deal of unstructured data like images and video might seek solutions specifically tailored to these materials. On the other hand, those working extensively with structured data like financial records may require tools that offer more advanced analytics capabilities.

• It is essential to choose a service provider with expertise in data warehouses and data lakes to manage structured and unstructured data, respectively.

Step 4 – Inspect Service Providers’ Data Governance Mechanism

Data governance refers to the overall management and control of data. It involves establishing policies, procedures, and frameworks to ensure data accuracy, integrity, availability, and compliance. When evaluating a service provider, consider the following:

• Assess their data governance frameworks: Inquire about the provider’s data governance policies, practices, and frameworks. They should have clear guidelines on data handling, metadata management, data lineage, data stewardship, and data quality management.

• Compliance with regulations: Verify if the provider adheres to relevant data privacy and security regulations such as HIPAA (Health Insurance Portability and Accountability Act), GDPR (General Data Protection Regulation), or any other industry-specific compliance requirements.

• Data ownership and control: Understand the provider’s stance on data ownership and control. Ensure that your organization retains full ownership of its data, and that the provider does not claim any rights over the data.

• Data access and authorization: Determine how the provider handles data access and authorization. They should have robust access control mechanisms to ensure only authorized individuals have access to sensitive data.

STEP 5 – Scalability and Flexibility

Scalability and flexibility are crucial factors to consider when choosing an enterprise data management service provider. Choose a service provider who offers the below provisions:

• Evaluate the provider’s ability to handle large and increasing data volumes. They should have the infrastructure and resources to accommodate your current data requirements and future growth projections.

• Assess the service providers’ performance under different workloads and peak periods. The provider should be able to deliver fast and efficient data processing, data integration, and analytics capabilities to support your business needs.

• Consider the provider’s storage capabilities. They should offer storage options, such as cloud-based storage, that can grow with your data requirements without compromising performance or incurring significant costs.

• Assess the provider’s ability to integrate with your existing systems and technologies. The solution should support various data sources, formats, and protocols, allowing seamless integration with your data ecosystem.

• Ensure the provider’s solution aligns with your technology stack and future roadmap. It should be compatible with your preferred databases, programming languages, and analytics tools, allowing seamless integration and interoperability.

Step 6 – Insights and Analytics Capabilities

• Determine whether the provider offers advanced analytics techniques such as machine learning, predictive analytics, natural language processing, or data mining. These techniques can help derive valuable insights from your data and enable data-driven decision-making.

• Evaluate the provider’s data visualization tools and reporting capabilities. They should offer intuitive and interactive visual reports that allow users to explore and present data in a meaningful and actionable way.

• Determine whether the provider offers prescriptive analytics capabilities. Prescriptive analytics goes beyond predictive and descriptive analytics by suggesting actions and providing recommendations based on the analyzed data.

• Determine whether the provider supports real-time or near-real-time data analytics. Real-time analytics lets you derive insights from streaming data, enabling proactive decision-making and immediate actions.

Read More – Data Science in Healthcare

Step 7 – Cost and ROI

• Evaluate the initial costs of implementing the data management solution, including licensing fees, implementation costs, and any necessary infrastructure investments.

• Consider the recurring costs involved in using the service, such as subscription fees, maintenance fees, and support costs. Assess if the pricing structure aligns with your budget and if there are additional costs for data storage, processing, or transfers.

• Determine if there are any cost implications as your data volumes and processing requirements increase. Understand if the provider’s pricing model accommodates growth or if there are additional charges for scaling up.

• Determine how the data management solution can deliver tangible business value. Assess how it can improve operational efficiency, enable better decision-making, enhance customer experience, drive revenue growth, or reduce costs.

Benefits of Outsourcing Enterprise Data Management to Experienced Service Providers

1. Access to Expertise: Outsourcing data management allows organizations to tap into the expertise and experience of specialized service providers. These providers are dedicated to data management and have a deep understanding of industry best practices, emerging technologies, and regulatory compliance. They can bring valuable insights and knowledge to effectively handle and optimize data that may not be readily available in-house.

2. Focus on Core Competencies: By outsourcing data management, organizations can focus on their core strategic initiatives. Data management can be complex and time-consuming, requiring dedicated resources and expertise. Outsourcing allows internal teams to concentrate on their primary business functions, improving efficiency and productivity.

3. Upfront Innovation: Data management service providers stay up-to-date with the latest technologies, tools, and methodologies in the field. They continuously invest in R&D to improve their offerings and incorporate emerging trends, such as AI, machine learning, and big data analytics. By outsourcing, organizations can benefit from the provider’s ongoing innovation, ensuring access to the latest advancements without the burden of constant upgrades and maintenance.

Choose Zuci Systems for Enterprise Data Management Service

Zuci is a highly regarded outsourcing partner specializing in comprehensive data management solutions. Allow us to propel your business forward with our advanced data management system. Contact us to discover the precise ways in which we can assist your enterprise with its data needs.