HomeData EngineeringData NewsMaking Business Sense of AI-Unified Data Analytics

Making Business Sense of AI-Unified Data Analytics

Some of the more revolutionary technologies of today include big data and artificial intelligence (AI). Many organizations have invested in them as a result of the numerous think pieces that have discussed their potential, yet many AI and data projects fall short of expectations. This problem is resolved by AI-unified data analytics.

For data analytics to be effective, a great amount of information must be gathered from various sources. AI is frequently the same. By combining these various data sources and analytics pipelines into a single platform, unified analytics automates the process. Here is how your firm might benefit from this automation and consolidation.

1. It Brings Costs Down

One of the major issues with big data analytics is IT sprawl. According to a survey, 43% of firms utilize four to six platforms now to handle their information, while 11% use more than ten. That can rapidly get pricey.

You may get the same information by combining your data into a single platform rather than paying for six or more providers. Your associated infrastructure can also be reduced. You can manage all of your data using the same security and governance technologies if there are fewer silos and separate databases.

By shortening timescales, AI-unified data analytics also reduces expenses. The information cleansing and analysis process can be automated to get answers more quickly and get a quicker return on investment.

2. It Offers More Reliable Information

In comparison to older, more traditional, fragmented systems, unified analytics is also more precise. Making solid judgments requires more than just having the proper facts. Additionally, you must comprehend your data in its context, which is much simpler when everything is visible in one place.

You may analyze it all at once by integrating your data collecting and analytics operations. This unification is crucial for making the best decisions since information from one database may influence how you understand another.

You might be able to take into account facts that you might otherwise overlook by removing silos. Dark data—information that is gathered but never used—makes up 80% of all data in businesses. By removing the old barriers that prevent you from seeing and using this information, you may make judgements that are more reliable since they are based on all the information that is available.

3. It Enhances Productivity

You can increase your efficiency by using AI-unified data analytics for automation and consolidation. AI can automate the most time-consuming, repetitive processes so that employees don’t have to move between as many programs. You can have a lot more time in a year with even little improvements in these areas.

‘Unified analytics’ enhanced decision-making will also be beneficial. Employees that are comfortable making decisions have higher productivity and engagement levels, which enable them to do more. AI taking over boring tasks will further increase employees’ enthusiasm for their jobs.

4. It simplifies regulatory compliance 

Easier regulatory compliance is a benefit of AI-unified data analytics. Data regulations like the GDPR and CCPA are growing more prevalent, yet it can be difficult for firms to comply with them. It is challenging to see what information you have and how to obtain it due to siloed data and fragmented workflows, but unification enhances transparency.

You can better understand your data and analytics pipelines by consolidating them all in one place. This makes it easier to identify possible compliance problems and put into practice good governance policies.

Any modification that needs to be implemented across fragmented data processes takes time and may be costly. You can save time and money by consolidating them using unified analytics so that you only need to deploy modifications once to use them throughout the entire enterprise.

5. It is more scalable 

Big data and AI are more scalable thanks to unified analytics. Data is expanding at an exponential rate, and by 2025, it is anticipated that total volumes will surpass 180 zettabytes. A scalable analytics solution is required if you want to continue profiting from this growing volume of data.

Individually scaling siloed processes and technology is challenging and expensive. On the other hand, if you manage everything on a single platform, you can easily extend or contract it as needed. You may make the most of fresh data collecting and analysis efforts by utilizing AI’s quicker ROIs.

As data volume increase, effective analytics will generate more and more important insights. To take advantage of that, you’ll need unified analytics’ scalability, which is necessary to stay competitive.

Unified Data Analytics Unlocks the Potential of Your Data

Because of the unnecessary complexity of their analytics procedures, many firms are unable to fully utilize their data. A better path ahead is provided by AI-unified data analytics, which enables you to utilize all of your data efficiently.

Unified analytics will become more significant to firms as data does. By putting these procedures into practice today, you can ensure future success.

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