Given the ever-evolving technological advancements, it is no surprise that information has become the very essence of every business setup. However, it has also paved the way for proliferation in massive volumes and formats, from numerous sources, at differing paces, and with varying relevance. This has made professionals shift from data scarcity to data overload. Moreover, this abundance demands a whole new level of investment in terms of time, energy, cost, and effort to gather, store, process, organize, retrieve, and interpret data, becoming a key reason for dwindling productivity and soaring business losses.
Enterprises employ various methods to operate, manage, and utilize the data they generate or acquire. However, coping with the barrage of technical jargon like data analysis, data management, data structuring, data governance, and data integration can be challenging.
Two terms about data analysis often used interchangeably are data integration and data management. Though used synonymously, these processes differ from one another significantly.
Read ahead to understand what they mean and how they differ from one another.
What is Data Integration?
Data integration is nothing but technological and business methods for combining data from many sources to answer critical issues. By aligning, combining, and presenting each data storage to an end-user, this method generally aids the analytic processing of data. Data integration enables businesses to understand better and retain customers, foster cross-departmental collaboration, shorten project time frames via automated development, and manage compliance and security.
Consider making a decision based on inaccurate or incomplete information. For instance, if you are to make a financial decision involving multiple departments and employees but do not have all the relevant data pieces and information, you might fail to come up with the best outcomes. Now extrapolate this situation and consider such ill-informed decisions made organization-wide. It now involves millions of rupees, thousands of data sources, and terabytes of data.
This is where the role of an integrated data platform comes into play. An integrated data platform is a service that brings data from multiple sources and accurately unifies them for business purposes. Data integration plays an indispensable role in the decision-making, strategy development, growth, and planning of businesses.
What is Data Management?
Today, data workers witness an information overload, making it critical to keep the data organized, collected, and optimized according to different business needs. And this can be achieved by implementing integrated data management processes. Data management includes everything about the organization and maintenance of data securely and cost-effectively. In addition to this, integrated data management also ensures the implementation of organizational guidelines, regulations and security standards regarding the handling and management of data, helping knowledge workers organize and securely maintain the data relevant to the business.
Since data is a vulnerable resource, every organization should have a data management strategy, which must be followed to keep uniformity throughout and keep the data safe. Making the most of technological development, organizations now employ cloud document management systems which are web-based data storage and management solutions that allow businesses to store, analyze, manage and interpret data online through cloud services. These cloud document management systems eliminate the heavy expenditure of setting up and maintaining traditional in-house servers.
Data Integration vs Data Management
From the definitions mentioned above, it must be clear that data integration and data management are two completely different processes businesses use to handle data. While about 50% of structured data is used in making decisions, only 1% of unstructured data is analyzed. However, knowledge professionals must realize that unstructured data makes up over 80%of the available data. And since inaccurate, incomplete, and wrongly analyzed data can adversely impact crucial processes, they must understand what makes these two processes differ from each other.
1. Organizations use different tools like integrated data platforms to unify data in one place. On the other hand, data management organizes and handles data using systems like cloud document management.
2. While data integration makes it easier to process and analyze data, data management deals with a much broader aspect of managing, safe-keeping, and refining the consolidated data.
Knowledge professionals must understand that data integration and data management are interrelated despite being two different data handling processes. Once integrated data platforms consolidate data into a unified system, integrated data management systems organize the data for easy access, retrieval and utilization.
The Way Forward
To make the most of the vast amount of data organizations own, they need to comprehend the criticality of having the processes streamlined and implemented in an organized manner. Therefore, the primary aim of employing solutions like an integrated data platform or cloud document management is to avoid being stuck in organizational silos and reduce considerable time and money loss.
Knowledge workers may now automate workflows and sift through information with ease because of Artificial Intelligence systems that operate on machine learning, cloud computing, and natural language processing. Managing data into a single repository has numerous advantages, from detecting a message encrypted in an image shared across a chat platform to identifying useful information in a pile of unstructured data from a conference call. Many time-consuming chores can now be completed with just a few clicks. Needl.Ai makes all this possible in a hassle-free manner.
A cloud-based AI platform that offers a unified view of all unstructured data across apps, Needl.ai offers a range of data processing and collaboration solutions. The platform is an error-free solution that enables data workers to achieve the highest level of productivity by collaborating seamlessly. Moreover, Needl.Ai offers services like cloud document management to help organizations escape the expenditure of setting up a dedicated hardware environment for data management. So, employ Needl.AI and find all your valuable data on a single platform, from your notes, emails, chats, and drives to public data such as commonly visited websites, subscriptions, and even bookmarks.
Leverage and unleash the potential of data with AI-powered data analysis systems.