Data analytics is a powerful tool that can help organizations reach their strategic goals. By leveraging data-driven insights, organizations can gain a clear understanding of their customer base, identify new opportunities, and make informed decisions. With the right tools and strategies in place, businesses can capitalize on the power of data analytics to achieve success in today’s competitive landscape.

Data analytics and Artificial Intelligence can help companies maximize their data potential & bring about new business insights. Here are some tips to get you started on this journey of data exploration. We are living in an era of data explosion, and the need for robust & scalable platforms for collecting, managing, and analyzing this data is growing every day. 

Companies have to be ready to tackle these challenges and make full use of their ever-expanding data resources. Companies are realizing the incredible business potential of data analytics & AI technology. Also, coupled with digital transformation, it provides an amazing opportunity for business leaders to unlock their fullest potential. 

Some of the findings are:

      • Digital transformation programs are gaining widespread popularity, with 80 percent of organizations expediting their initiatives.
      • An impressive 79 percent of companies are now taking advantage of the latest technologies to re-invent their business models.
      • A vast majority of organizations have acknowledged the need for more adaptive and responsive IT infrastructure due to recent changes in their industry.

To thrive in this era, businesses have to pivot from their old methods and create a new technological environment – which works across the edge, core, and cloud. It’s a crucial move for success. Data analytics and AI have been providing immense value to businesses in a range of areas. Starting on this journey can be beneficial as the opportunities are endless.

The path to data analytics and AI

Starting with data analytics is as easy as taking on any other IT project. A strategic plan should be set in place and followed step-by-step until the desired solution has been deployed. This process can help optimize data analytics use within companies of different sizes and industries. Taking full advantage of data analytics and AI in your business can be a daunting task. However, with the right knowledge and approach, you can make considerable strides towards achieving this goal. Here is a brief overview of one possible path to do so.

      • Planning for the journey

Taking the leap towards a data-driven organization, leveraging data analytics and AI for insights, is a process. Before you begin this journey, it’s imperative to have a clear vision of what lies ahead, as well as an action plan in place to achieve your desired outcomes from data. The action plan should include essential steps in the data analytics journey, such as: gathering data, analyzing it & creating actionable insights. It is pivotal to ensure that each phase is thoroughly thought through and planned.

      • Beginning the journey

Companies are taking the necessary steps to take advantage of data by consolidating it and using it for their benefit. Putting the right data platforms in place is a critical step in this process, which can help businesses make better decisions. Apache™ Hadoop® offers fantastic advantages for data storage and analysis. It’s especially useful because it can store any type of data from any source, cost-effectively, and at a large scale. This is a tremendous benefit for businesses. AI makes it easy and fast to conduct complex data analysis and transformations, which can be immensely useful.

      • Consolidating data for analytics

Many organizations struggle with this step — either to begin the data analytics journey or to make data consolidation projects successful once they’ve begun. Organizations are often impeded by a lack of Hadoop expertise and end up spending too much time and effort on the front-end work before they can get to the results of a fully operational solution.

To avoid these pitfalls, it’s important to partner with organizations that offer both expertise and infrastructure for data consolidation. Businesses that operate in the same industry should consider partnering with an organization that can provide data consolidation, especially if you have a large volume of data. The more similar the partners are, the easier it will be for them to work together. For example, if one company provides accounting services and another offers insurance services, it’s easier to combine their data because they’re both in the same industry.

They are driving digital transformation with data analytics and AI.

Gain from using Data analytics and AI

Organizations have a lot to gain from using data analytics and AI, which can be classified into two broad categories: improving operational efficiency and transforming the business.

AI is making many businesses more efficient with use cases such as optimizing warehouse data, consolidating repositories, exploring data, performing analytics and preserving archives. Moreover, it is enabling companies to transform their operations by helping them develop models to manage risk, improve products, and analyze customer behavior & loyalty better.

It is essential to recognize the data-driven use cases that are significant for your organization and prioritize them in your journey with data analytics. That way, you can be sure to make the most out of it.

Key takeaways

To stay competitive today, organizations must transform the people and processes involved, as well as their IT environment – from the edge to the cloud. Such a transition can be beneficial for businesses and help them succeed in this ever-changing digital age. Data analytics & AI are revolutionizing the business world and presenting us with a wealth of opportunities. Don’t hesitate to take advantage of this transformation, starting today! 

Get in touch with Chapter247 and learn more about how we can incorporate the power of data analytics in your business and reach your strategic goals. Click here to know more. 

Data Analytics, Data Engineering, BIog Data, Staff Augmentation, Artificial Intelligence, IT strategy