Augmented Analytics Market Will Grow Due to the Increasing Volume of Data | Salesforce, SAP, IBM, Microsoft, Oracle

Augmented analytics is a data analysis technique that combines human intelligence with artificial intelligence (AI) to enhance the decision-making process. The goal of augmented analytics is to make data analysis more efficient and effective by automating repetitive tasks and providing more insights in a shorter amount of time.

Augmented analytics can be used for a variety of purposes, including identifying trends, predicting future outcomes, and providing recommendations. The technique is often used in business intelligence, marketing, and financial analysis.

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Key Trends

There are four key trends in augmented analytics technology:

1. The rise of artificial intelligence (AI) and machine learning (ML)
Augmented analytics is powered by AI and ML technologies, which are becoming more sophisticated and widely adopted. AI can help identify patterns and trends in data that would be difficult for humans to find, while ML can automate the process of creating predictive models.
2. The increasing popularity of cloud-based solutions
Cloud-based augmented analytics solutions are becoming more popular, as they offer flexibility and scalability. These solutions can be deployed quickly and easily, without the need for on-premises hardware or software.
3. The need for data governance and security
As augmented analytics solutions become more widely used, there is a greater need for data governance and security. These solutions often access and analyze sensitive data, so it is important to ensure that only authorized users have access to the data and that it is properly protected.
4. The demand for more user-friendly solutions
There is a growing demand for augmented analytics solutions that are more user-friendly, as businesses look to make data-driven decisions without the need for specialized skills or training. User-friendly solutions often have an intuitive interface and require minimal setup.

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Key Drivers

There are several key drivers of the augmented analytics market. First, the increasing volume of data is creating a need for more sophisticated methods of analysis. This is especially true in the Big Data era, when organizations are dealing with large data sets that are difficult to analyze using traditional methods.

Second, the need for faster and more accurate decision-making is driving the need for more advanced analytics. Organizations are looking for ways to gain insights more quickly and accurately in order to make better decisions.

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Third, the increasing adoption of cloud computing is providing a more cost-effective and scalable infrastructure for augmented analytics. Cloud-based solutions are often more flexible and easier to implement than on-premise solutions, making them attractive to organizations of all sizes.

Finally, the increasing popularity of mobile devices is providing a new platform for augmented analytics. Mobile devices are becoming increasingly powerful and are capable of running sophisticated applications. This is providing new opportunities for organizations to use augmented analytics to improve their decision-making processes.

Market Segmentation

The Augmented Analytics Market is segmented into deployment, application, end-user and region. By deployment, the market is divided into on-premise and cloud. By application, the market is classified into sales & marketing, finance, IT, operations, and others. By end-user, the market is bifurcated into retail, BFSI, manufacturing, government, and others. By region, the market is classified into North America, Europe, Asia-Pacific and rest of the world.

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Key Players

The key players in the Augmented Analytics Market are Salesforce , SAP , IBM , Microsoft , Oracle , Softengi, MicroStrategy , SAS , Qlik and TIBCO Software

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