How AI-Augmented Data Management Evolves In 2022?
According to IDC, data is rising globally, from 45 zettabytes in 2019 to a predicted 175 zettabytes by 2025.
Increased internet access, broadband access, mobile phone use, and social media use are among the causes of global data growth. With rapid growth, data has become the key driver for almost every enterprise decision and business strategy. A business is all about taking risks, but it doesn’t mean you follow opportunities blindly.
According to a Forrester report, data-driven businesses are growing at an average of more than 30% yearly.
Businesses are embracing the power of data and becoming data-driven to grow rapidly in the ever-changing tech-powered world. Data-driven organizations make use of advanced tools and software to collect data in bulk. Although data is available in abundance, and companies often collect it at a large scale, it is critical to further manage and refine it so that it has genuine use to different teams of a company
To treat data as a valuable resource and asset, you need an effective data management strategy. Data management is a crucial part of a business. It involves a broad range of strategies, concepts, and procedures aimed at maximizing the value of data assets while remaining compliant with data standards. Today almost every company, be it a start-up or an established corporation has data management tools and a team to look after its company’s data needs. The team includes data administrators, programmers, data strategists, chief data officers, and other related professionals. Together they work to transform the raw data into accurate, relevant, and usable data for the enterprise. Businesses also prefer to outsource data management service providers from a third-party company. Using the most advanced tools and technologies they keep your data managed.
Interestingly, the technology which has brought the evolution in Data management or Enterprise Data Management (EDM) is Artificial Intelligence. We all know that proper Data management has huge benefits for a company, however with AI the process is even more efficient, accurate, scalable, and productive enabling companies to reap more benefits from EDM. Let’s see How AI has brought the evolution in Data management in 2022?
What is Data Management?
Every day, massive amounts of data are generated.
By 2025, individuals are expected to produce 463 exabytes (one exabyte = one billion gigabytes) of data each day on a worldwide basis.
The majority of the data is generated through social media, digital services, IoT, and communication. This data needs to be properly maintained. Managing information effectively will guarantee that crucial data is never lost, and you will avoid the disastrous consequences that occur with data loss. Data management (DM) is defined by Gartner as “the practices, architectural techniques, and tools for achieving consistent access to and delivery of data across the enterprise’s spectrum of data subject areas and data structure types to meet the data consumption requirements of all applications and business processes.” Data management helps in the effective and long-term digital transformation of an organization, increasing the value of data while lowering expenses. With the right data management solutions, companies can have the needed data insights for making decisions. To avoid data loss and error, companies are hiring data management service providers. Using AI-powered tools, they offer efficient and error-free data management solutions to their customers. Artificial Intelligence has a considerable impact on the accuracy and speed of data management.
Artificial Intelligence Has Transformed Data Management
AI has the ability to change practically every area of people’s lives, including how they work, learn, travel, and engage in multiple activities. Artificial intelligence (AI) is the product of the combination of diverse fields such as psychology, computer science, biology, and linguistics. However, in order to fully benefit from AI’s capabilities, businesses must also incorporate AI at the data level. AI can support the whole data management lifecycle, from scraping to management. In this smart machine age, AI can simply optimize, and automate data management, quality improvement, governance, metadata management, and enterprise data analytics processes. AI is found to make serious advancements in data management processes when embedded throughout the EDM environment.
A deep dive into different companies’ opinions of using AI, 451 Research found that nearly 90% of the data-driven companies agree that AI and ML are important components of data platforms and analytics initiatives.
It is a challenging task to turn the raw data into accurate and insightful data to further provide it to data consumers of the enterprise, particularly data analysts and data scientists. To become ‘Data-Rich,’ mine ‘Gold’ out of your database with the right strategy. Infusing Artificial Intelligence into the data management process can accelerate this process, improve data quality and accuracy and increase data safety. There are many data management service providers who can help you derive maximum value out of your business data with the help of AI. With the best AI-powered Data Management Solutions, you can reduce data complexity, clean data downstream, take control of your core business information, handle complex data, overcome poor data quality and optimize data. Below are the few important aspects of Data management that have evolved by AI applications
Improve Database Query Accuracy & Performance
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.
Access To High-Quality Data To Every Data Consumer
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.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.
Improved Productivity Of Data Analysts And Data Scientists
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.
Impact Of AI On Industrial Data Management
There is no industry that is not using AI applications to improve their data and IT processes, specifically data management. Humans are generating a lot of data each passing day and the number is increasing rapidly. Data is no longer the exclusive domain of technology firms. Data is already being used by businesses including healthcare, eCommerce, hotels, and education to improve marketing tactics, improve customer experience, evaluate competitors’ growth, and simply collect insights on user data. An increasing amount of data in a business database demands the need for management. AI is empowering data management to become more accurate, efficient, and responsive. AI-powered data management has been transforming multiple business industries including
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.
Digitization of data management is the ultimate way to keep it safe, accurate and well-maintained. Businesses in different industries are incorporating AI in the data management process. When AI is integrated into data management software, it helps to simplify, optimize, and automate data management procedures. Traditional data management setups are incapable of keeping up with new analytics projects like big data. The world of analytics is being transformed by AI and machine learning. Modern data management service providers are also using AI because it makes EDC considerably easier to utilize for non-technical workers by automating the discovery process. If you want to accelerate data management in your business, you can choose Outsource Bigdata’s AI-Augmented EDM service. It is a trusted name in delivering world-class data solutions. Outsource BigData is serving global customers with its affordable and high-quality data management services. Using the most advanced tools and technologies, professional data managers at Outsource BigData are delivering satisfying data management solutions to businesses in different industries. To know more, visit the official website of Outsource BigData.
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As part of AIMLEAP Business, AIMLEAP Outsource Bigdata practice provides advanced data collection and management expertise, as well as Robotic Process Automation (RPA) capabilities that help clients create highly personalized digital experiences, products and services. Our RPA solutions help customers with insights from data for decision-making, improve operations efficiencies and reduce costs. To learn more, visit us www.outsourcebigdata.com