Scope of Global Data Management Industry Reports-
Data management is an administrative process needed to guarantee the accessibility, dependability and timelessness of data for its users, by acquiring, validating, storing, protecting and processing acquired data. To leverage massive amount of data that organizations are collecting, analyzing and storing, companies are adopting to data management solutions and platforms, as it makes processing, validation and other management functions simpler and less time consuming. major data management platforms provide enterprises, a 360-degree view of their customers and the complete visibility required to have deep, critical insights into consumer behavior that make brands more competitive.
Global Data ManagementIndustry Market is valued at USD 64.315billion in 2019 and expected to reach USD 128.028 billion by 2026 with the CAGR of 10.34% over the forecast period.
GlobalData ManagementIndustryDynamics –
Increasing competitive business which depending more on data analysis, growing data explosion both structured & unstructured, increasing requirement of compliance with data regulations, growing pressure from customers to provide accurate customer service and rise in perception of data as corporate asset are driving the global data management industry. For instance, 98% of companies are now using data to improve customer experience, as now more than ever, customer experience is deemed as competitive advantage and revenue driver for many companies. Additionally, flood of data into business even if provides opportunities for good customer engagement, these data come up with inaccurate data and about 69% of companies agree that this inaccuracy is disadvantageous to their ability in providing excellent customer service. To mitigate this problem, organizations are increasingly adopting data management solutions boosting the data management industry. In enterprises, IT is managing data in about 84% of cases, but now, in terms of driving change through data management projects, business owners are beginning to get involved. At present, IT teams are only leading in decision making through data management in 53% of cases, with 28% claiming it’s a combination of departments, and 24% of cases, the Chief Data Officer’s team drives them. These types of Changing data ownership are expected to create more opportunity in data management industry. lack of proper data management can burden organizations with incompatible data storage, unreliable data sets and bad data quality that weaken their ability to run business intelligence (BI) and analytics applications and may lead to faulty findings, for which data management is becoming more imperative for the organizations in this data explosion era. The importance of data management industry has also grown, due to businesses being subjected to an increasing number of regulatory compliance requirements, data privacy and protection laws such as GDPR and the California Consumer Privacy Act. Additionally, companies are collecting large volumes of data and a great variety of data types. Without appropriate data management, such high data intense environments can become cumbersome and hard to navigate.
Recent Development-IBM adds AI-fueled forecasting to Planning Analytics platform
On 20 May 2020, IBM added a new feature to its Planning Analytics portfolio with the introduction of Planning Analytics On Demand. The new feature is envisioned for SMBs and enterprises wanting to change individual departments from manual budgeting and forecasting processes to an automated, AI-powered process.
Many companies, still depend on manual processes using spreadsheets for budgeting and forecasting, comprising demand planning, salary planning, merchandise planning etc. and when done manually, this process takes days or even weeks. Enterprise planning systems like Planning Analytics On Demand expects to bring that time down to hours.
Planning Analytics On Demand is made to permit a user to sign up and get running quickly. It has a preliminary price of USD 45 per month for one authorized user and a single 2GB application database, and extra users can be brought on for USD 40 each. The software applies natural language processing to capture and analyze human language data and then suggests improvements to the planning process. Other machine learning capabilities support clients in creating what-if modeling scenarios without turning to a data scientist.
The software can create models, workbooks, invite others to participate, similar to a system that was managed by their systems team, but now these software can do it self-service on their own.
Data Management Industry Trends 2020
Protecting Data with the Help of Artificial Intelligence:
Use of Artificial intelligence for security purpose is a trend in data management industry in 2020. One of the latest applications in the world of AI is using this methodology to enhance data security. Many businesses collect data from a number of varied channels or touchpoints. These touchpoints generally comprise things like websites, mobile devices and even devices powered by the Internet of Things (IoT). For instance, by 2020, over 20 billion IoT devices will be active in technosphere which will create massive amount of data and can jeopardize the security of company’s system also. With the application of artificial intelligence, an IT team can protect a database with ease, which will be incorporated more in data management industry.
Augmented Data Management:
Augmented data management is another technology which is trending in 2020 in data management industry. Augmented data management enables users to do tasks like schema recognition, regulatory compliance, and utilization easily. This innovative science changes metadata from passive auditing and reporting systems to active driver of AI or ML systems. Rather than dealing with the mistakes that will arise by doing analytic jobs manually, clients are thinking to use augmented data management tools for their business, which bolsters the data management industry. Surveys show that enterprises will decrease their dependence on manual data entry and verification by about 50% in the next three to four years by enabling IT professionals to weigh in on which tools to use for augmented data management.
Persistent Memory Servers are Becoming Popular:
Persistent memory servers are trending in the data management industry due to perception of data as an asset to bolsters the business. When trying to expand the brand & product a company has, collecting tons of new data is important. With this data, an enterprise will have no problem developing data-driven marketing campaigns. The more data a company collect, the harder it will be to keep its cloud-based servers fast and functional. For this reason, many third-party cloud server providers are beginning to use persistent memory servers.
These servers enable business owners to analyze data in real-time without using a lot of bandwidth. It is estimated that by the year 2021 persistent memory servers will be applied in over 10 percent of the cloud-based servers on the market. With the application of this memory server, enterprises will have relatively less problem collecting and analyzing tons of data in a short amount of time, which will help the data management industry to be more popular among end users.
Gain Better Insights with the Help of Augmented Analytics:
Augmented analytics is one of the popular trends in the data management industry in 2020. Augmented analytics allow enterprises and their team to get real-time information from the data being collected. This data can be applied for everything from consumer engagement to making important strategies on the direction a business is going to take. And augmented analytics is used mainly to analyses the data automatically with least help from IT professionals. It uses both natural language processing and machine learning to augment the analytics collected from enterprise’s data. This augmented methodology is also used for things such as business intelligence and data sharing.
In next generation analytics platforms, innovative ML techniques will be applied to totally control the analytics process from development to consumption. Analytics vendors are starting to compete on this technology in 2020. It is estimated that, the augmented analytics market is expected to grow by about USD 18.4 billion globally, which also bolster the data management industry.