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Challenges Of Managing Enterprise Data

Updated: Jun 28, 2022

Challenges Of Managing Enterprise Data

Data is the lifeblood of the digital economy. Businesses worldwide rely increasingly on data to run their daily operations and make informed business decisions. Big business houses (and even many small and midsize businesses) are continuously dealing with highly sophisticated IT systems that are often dispersed across multiple geographies and sovereignty regulations. With so much data being generated, handling data across a company, which may be scattered over various geo-locations, has become challenging. Data management challenges can cause a slew of problems such as poor risk management decisions, security breaches, privacy violations, unlawful access, data silos, noncompliance with regulations, an uncontrolled environment, a restricted number of resources, etc.

Data is the backbone of any business. Big business houses rely entirely on data to make decisions for their organizations. Discovering the value of data opens up enormous prospects for companies. It is critical to have well-defined data management plans to meet the most challenging difficulties that data management entails.

The Most Common Challenges In Data Management Are :

The Most Common Challenges In Data Management Are


The first problem in managing data is to keep information consistent across multiple systems when it is updated. Data must be of good quality for business intelligence to make it useful. This means that data must be entered into the system in a consistent, timely, and predictable manner.


It is predicted that daily, 2.5 quintillion bytes of data are generated. Just imagine from where this data is produced? Companies generating this exponential amount of data face many issues in terms of data acquisition, maintenance, and value generation. The greater the amount of data collected, the more inspection and evaluation are necessary. By effectively managing their data, companies can have greater insight into consumer behavior and market trends, helping them to make more powerful judgments, improve procedures, improve marketing campaigns, and optimize products and services.


This is one of the most serious challenges of data that every business faces. Large companies may end up with several business solutions, each with its own data repository, including databases, CRM, ERP, etc. Storing and handling large data repositories often creates barriers for the businesses that need to be properly addressed to analyze and manage them. It's tough to find and integrate data on a universal data platform to speed up data-driven decisions when data is housed in distinct siloed systems. A company's top priority should be to create a single source of truth for its data by removing data silos and integrating data from users, products, and suppliers.


Data quality is one of the most serious concerns many businesses are dealing with nowadays. Most firms use a database to keep track of information, but ensuring data quality when processing or recording data is tough. Data collected must be free from errors. Enterprises are oversaturated with data, and over 50% of their estate data is dark, making it difficult to determine what data they have, why they are retaining it, what their sensitivity is, and how to utilize it best. Companies like Zantaz, through specialized enterprise services like Zantaz Detect Storage Optimization Program, simplify enterprise data management by remediating data stores, optimizing data storage costs, and identifying sensitive content for proper preservation and security.


The ultimate objective of getting quality-ready data is to use it for further analysis and processing by other business intelligence tools so that it can be sent to senior management for better decision-making.


Data is a very important asset obtained after extensive research and allocation of resources. It contains sensitive information that could hurt the business and its customers in various ways. Data breaches can be avoided by properly safeguarding the data using cutting-edge technology and understanding how and by whom this data can be accessed. A team of data security professionals is required to safeguard sensitive data and prevent unauthorized access. It also looks for unintended movement, deletion, or other obstructions. Zantaz with Zantaz Detect and Data Management services maintains and improves organizations' security posture by identifying sensitive data and enacting and creating policies to quarantine and manage this data.


The data collected from different sources may be of good quality but have little relevance without proper analysis. data is regularly analyzed by data experts in order to derive true value from data and to put it to use. With the advancement in technology, large amounts of data can be easily analyzed, but the organization still requires proper analysis tools to maintain the quality of data. There are a number of sophisticated tools available that assist the business in importing data and evaluating it to know the true relevance of data.


According to research, 80% of data collected is in an unstructured form. This data is of no use to the organization whether the data collected is of good quality. When collected, the data is usually in unstructured form, so organizations must analyze it carefully to derive value from it. The ability to transfer unstructured data into a structured form is crucial for organizations to survive in this competitive business environment. Zantaz's suite of services and solutions offers data analysis of unstructured data to improve data quality and transform data for structured solutions.


Data governance is responsible for defining rules and regulations for an organization's information state. The data governance framework is just like a constitution that helps implement policies, procedures, and rules related to data. In order to meet specific federal standards and requirements, an organization’s data governance plan should be prepared.


There is a significant shortage of experienced data experts immediately available for hire. These experts come with high salary packages as they are required in almost every organization to maintain solid data control and management. For a company that works with the latest technology, training entry-level employees will be costly. They must do a good job of retaining these employees once they have acquired this skill set. Organizations are increasingly relying on automation, which includes cognitive technologies such as machine learning and artificial intelligence to develop data-driven insights.

Companies must be able to confront these data challenges to survive and flourish in this highly competitive business environment. Data must be managed actively throughout its existence, from creation to disposal. Actively managing enterprise data gives businesses more control over the data they collect and retain, which is advantageous. ZANTAZ EAS offers enterprises undergoing digital transformation, data consolidation, data capture, and cloud adoption projects. It also has the ability to orchestrate and manage data mobility within a single application. Zantaz delivers services and solutions that enable our customers to completely control their enterprise data estate for maximum value and utilization.

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