How AI-Augmented Data
Management Evolves In 2024?

AI-assisted database searching can significantly improve the overall accuracy of the query result. A query in a database is a request for data or information from a table or collection of tables. Enterprises can reduce the time it takes to create insight and enhance business choices by performing queries more efficiently. Artificial Intelligence is prominent for its feature of high accuracy. AI has a lot of potential for business leaders and what it may bring to their organizations’ future. Users want data management tools to completely comprehend their search inputs, context, and behavior, and to consistently deliver the correct results. Fortunately, delivering great query results no longer necessitates a large team. You must use AI-powered tools to improve database query accuracy & performance. AI-supported data management tools are self-learning tools that apply leading-edge data science techniques to query and deliver a real-time contextual understanding of each user, domain, and query.

In today’s environment, the explosion of data is quite omnipresent. Not only is there a large amount of data, but the growth of disruptive technology has taken over the industry. In the midst of this, it’s become critical for businesses to leverage the full potential of data. Not just that, the need for high-quality data has increased among businesses. Poor quality data proves to be expensive for businesses. How much harm can inaccuracy in data cause?  

In 1999, when NASA Mars Climate Orbiter approached the planet Mars, it lost contact with mission control. What is the explanation behind this? It caught fire in the planet’s atmosphere owing to a mathematical error induced by erroneous data. Two distinct software programs operated the Orbiter’s thrusters. The software on one thruster measured the amount of force required to attain an adequate height in pounds (lbs), whereas the second thruster interpreted the data in Newtons (N). The Orbiter cost NASA $125 million in all.  

This is an extreme example to be sure that inaccurate information can cause a huge loss to a business.  

The average financial cost of poor data quality on enterprises is $9.7 million per year, according to Gartner’s study. 

The incorporation of AI in data management helps users to access high-quality data for analysis and research. And that’s why modern data management service providers, are leveraging AI in data management to automate and accelerate the process.

When high-quality data is readily available, the research and analysis productivity of data analysts and data scientists are increased by a certain degree automatically. But accessing and preparing quality data is one of the most significant barriers. With the integration of developer tools and frameworks, an AI-enabled database may assist in overcoming this barrier to insight by speeding up data exploration and reducing development timelines. AI-powered tools present the information faster and more effectively. 

 When questioned about the advantages of AI, 61% of respondents stated it helped them be more productive and efficient at work.  

AI can uncover hidden insights in digital data by evaluating and retrieving essential data that the human eye would have missed. This way, the data analysts and data scientists are able to increase their productivity in researching and analyzing data. When you choose AI-powered data management tools, you can make better decisions based on quality data and rack up productivity gains. Today, a large number of data management service providers are harnessing the potential of AI to provide ready-to-use, high-quality, accurate data to customers.

The process of gathering, examining, and maintaining patient information in order to provide excellent treatment and other healthcare-related services to end-users is known as healthcare data management. In every industry, modern technologies are gradually taking over data management duties, and healthcare is no different. This industry is always brimming with patient information, medical records, and other vital information for patients and hospitals. AI-powered tools have been used To achieve data management objectives in healthcare sectors. AI handles medical data using advanced algorithms and strategies to execute different healthcare-related decision-making processes. The fundamental purpose of AI systems in healthcare is to ensure the links between preventative or recovery therapies and effects on patients’ health by checking on a regular basis. Diagnostic processes, clinical plan formulation, medication, personalized medicine, and patient tracking are all areas where AI technologies have been created and expanded. AI is also used to analyze everyday work like CT scans, X-rays, and other patient reports. Allowing AI to handle data enables patients to receive personalized therapies, which was previously impossible due to insufficient data management.  

According to figures indicating the worldwide market size for artificial intelligence in healthcare in 2016, 2017, and a forecast for 2025, the industry is expected to grow from around one billion dollars to more than 28 billion dollars.  

By adopting AI in data management, not just healthcare businesses, but patients are also achieving benefits.

Artificial intelligence (AI) in manufacturing is widely regarded as a key component of the so-called “new industrial revolution.” Every day, manufacturers generate thousands of TBs of data. For manufacturers, this information is precious, and it demands rapid attention, adequate preservation, and accessibility when needed.  

According to a recent analyst report, improper data management is thought to be responsible for a 27% revenue loss for businesses.  

In the manufacturing industry, data plays a major role, so it should be managed properly to avoid errors in the production line. AI drives and enables zero faults when paired with other digital technologies for data management. AI helps manufacturing companies in optimizing data management and eliminating revenue loss.  

The worldwide AI manufacturing market was worth USD 1.82 billion in 2019 and is predicted to reach USD 9.89 billion by 2027, with a CAGR of 24.2%. 

 In the fourth industrial revolution (4IR), disruptive technologies and trends such as robots, artificial intelligence, quantum computing, virtual reality, industrial internet of things (IIoT), and others are transforming the way we live and work. In fact, modern data management service providers are also using AI-powered tools to manage manufacturing business data with high accuracy and efficiency.

AI is now supporting the global real estate industry. Many real estate businesses are incorporating AI technology into their data pipelines and algorithms in order to make the right estimations and decisions. The digitization of documents has enabled real estate owners to increase their company’s productivity and efficiency to some extent. There are multiple data issues that need to be addressed in a real estate business. With the integration of AI, real estate businesses are able to manage data-related issues quite effortlessly. AI is assisting real estate brokers in the management of vast amounts of data such as legal documents, property assessment reports, sales information, ownership history, zoning rules, and so on. As it analyzes past sales statistics and selects properties that are most likely to sell, AI plays a vital role in generating potential leads. Clients typically desire properties they can’t afford, while real estate agents desire their ideal customers. A distinctive characteristic of AI is that it analyses thousands of attributes in the data to separate clients who are serious about buying a home from those who are just looking for fun.  It also aids in evaluating a property’s correct worth by examining current trends and tales. The effect of AI in the real estate industry is only going to grow in the coming years. The data management service providers are serving real estate customers for their data management needs by leveraging the power of AI.

Human Resources (HR) is one of the most important aspects of any organization since it is closely linked to the lives of the individuals who work for it. To be effective and productive, employees require a well-communicated and healthy work environment. Artificial intelligence, which is now one of the most advanced and rapidly developing technologies, has greatly helped in the improvement of the HR department. The bulk of HR duties is automated and completed by AI, allowing greater attention to be focused on the strategic scope of work. AI minimizes the time and effort necessary to execute tedious tasks, from screening applications to managing databases, scheduling interviews, and responding to and resolving contestant issues.  

According to research by Eightfold, HR staff who used AI software in order to complete administrative tasks are 19% more successful than those who did not.  

Deploying AI-powered data management software can ease the burden of the HR team. Real-time and reliable data is essential for optimal outputs in HR operations. So, it’s critical to get the right data first. By integrating AI-powered software into your database, managing data becomes easier. Real-time, high-quality, accurate data is what you get by using AI in your HR data management functions.

Any financial institution’s lifeblood is data, and the new generation of FinTechs is founded on it. Effective data management is required to extract value from data and use it in ways that improve the performance of FinTech business and the customer experience. Organizations can’t use all of the data they collect on a daily basis across channels, products, and services if they don’t have the right data management strategy. If financial organizations want to satisfy regulatory standards for security, privacy, and trust, they must have a strong AI-powered data management system. Businesses must ensure that their data is accurate, of high quality, and that they can obtain important information quickly enough to meet the deadlines and requirements of customers. Financial data should be kept secure from cyber threats and due to this, businesses are making use of AI for data management in the FinTech sector. AI data management also helps in keeping your data secure from unfriendly cyber threats.