Data Science Methodologies:Current Challenges and Future Approaches | Top 10 MBA Colleges in Bangalore

On 20/02/2023 09:57:03

There’s nothing constant in our lives but change. Over the years, we’ve seen how businesses have become more modern, adopting the latest technology to boost productivity and increase the return on investment. Data analytics, big data, artificial intelligence, and data science are the trending keywords in the current scenario. Enterprises want to adopt data-driven models to streamline their business processes and make better decisions based on data analytical insights.

With the pandemic disrupting industries around the world, SMEs and large enterprises had no option but to adapt to the changes in less time. This led to increasing investments in data analytics and data science. Data has become the center point for almost every organization.

As businesses rely on data analytics to avoid and overcome several challenges, we see new trends emerging in the industries. AI trends 2023 by Gartner are an example of development. The trends have been divided into three major heads- accelerating change, operationalizing business value, and distribution of everything (data and insights).

In this blog, we’ll look at the most important data science trends in 2023 and understand how big data and data analytics are becoming an inherent part of every enterprise, irrespective of the industry. top 10 mba colleges in bangalore

1. Big Data on the Cloud 

Data is already being generated in abundance. The problem lies with collecting, tagging, cleaning, structuring, formatting, and analyzing this huge volume of data in one place. How to collect data? Where to store and process it? How should we share the insights with others? good mba colleges in bangalore

Data science models and artificial intelligence come to the rescue. However, the storage of data is still a concern. It has been found that around 45% of enterprises have moved their big data to cloud platforms. Businesses are increasingly turning towards cloud services for data storage, processing, and distribution. One of the major data management trends in 2023 is the use of public and private cloud services for big data and data analytics. online mba colleges in bangalore

2. Emphasis on Actionable Data 

What use is data in its raw, unstructured, and complex format if you don’t know what to do with it? The emphasis is on actionable data that brings together big data and business processes to help you make the right decisions.

Investing in expensive data software will not give any results unless the data is analyzed to derive actionable insights. It is these insights that help you in understanding the current position of your business, the trends in the market, the challenges and opportunities, etc. Actionable data empowers you to become a better decision-maker and do what’s right for the business. From arranging activities/ jobs in the enterprise, streamlining the workflows, and distributing projects between teams, insights from actionable data help you increase the overall efficiency of the business. mba colleges in bangalore list

3. Data as a Service- Data Exchange in Marketplaces

Data is now being offered as a service as well. How is that possible?

You must have seen websites embedding Covid-19 data to show the number of cases in a region or the number of deaths, etc. This data is provided by other companies that offer data as a service. This data can be used by enterprises as a part of their business processes. best mba colleges in bangalore

Since it might lead to data privacy issues and complications, companies are coming with procedures that minimize the data risk of a data breach or attract a lawsuit. Data can be moved from the vendor’s platform to the buyer’s platforms with little or no disturbance and data breach of any kind. Data exchange in marketplaces for analytics and insights is one of the prominent data analytics trends in 2023. It is referred to as DaaS in short.

4. Use of Augmented Analytics

What is augmented analytics? AA is a concept of data analytics that uses AI, machine learning, and natural language processing to automate the analysis of massive data. What is normally handled by a data scientist is now being automated in delivering insights in real-time.

It takes less time for enterprises to process the data and derives insights from it. The result is also more accurate, thus leading to better decisions. From assisting with data preparation to data processing, analytics, and visualization, AI, ML, and NLP help experts explore data and generate in-depth reports and predictions. Data from within the enterprise and outside the enterprise can be combined through augmented analytics.

5. Cloud Automation and Hybrid Cloud Services

The automation of cloud computing services for public and private clouds is achieved using artificial intelligence and machine learning. AIOps is artificial intelligence for IT operations. This is bringing a change in the way enterprises look at big data and cloud services by offering more data security, scalability, centralized database and governance system, and ownership of data at low cost.

One of the big data predictions for 2023 is the increase in the use of hybrid cloud services. A hybrid cloud is an amalgamation of a public cloud and a private cloud platform.

Public clouds are cost-effective but do not provide high data security. A private cloud is more secure but expensive and not a feasible option for all SMEs. The feasible solution is a combination of both where cost and security are balanced to offer more agility. A hybrid cloud helps optimize the resources and performance of the enterprise.

6. Focus on Edge Intelligence 

Gartner and Forrester have predicted that edge computing will become a mainstream process in 2023. Edge computing or edge intelligence is where data analysis and data aggregation are done close to the network. Industries wish to take advantage of the internet of things (IoT) and data transformation services to incorporate edge computing into business systems.

This results in greater flexibility, scalability, and reliability, leading to a better performance of the enterprise. It also reduces latency and increases the processing speed. When combined with cloud computing services, edge intelligence allows employees to work remotely while improving the quality and speed of productivity. MBA College in bangalore with Business Analytics 

7. Hyperautomation

Another dominant trend in data science in 2023 is hyper-automation, which began in 2020. Brian Burke, Research Vice President of Gartner, has once said that hyper-automation is inevitable and irreversible, and anything and everything that can be automated should be automated to improve efficiency.

By combining automation with artificial intelligence, machine learning, and smart business processes, you can unlock a higher level of digital transformation in your enterprise. Advanced analytics, business process management, and robotic process automation are considered the core concepts of hyper-automation. The trend is all set to grow in the next few years, with more emphasis on robotic process automation (RPA). top mba colleges in bangalore

Conclusion 
Data science will continue to be in the limelight in the coming years. We will see more such developments and innovations. The demand for data scientists, data analysts, and AI engineers is set to increase. The easiest way to adopt the latest changes in the business is by hiring a data analytics company.

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