What Are Data Analytics Consulting Services?

Data Analytics Consulting Services are the latest addition to Business Analytics. Data Analytics Consulting Services employs a variety of techniques to optimise various business intelligence tasks by leveraging existing data.Business analytics has opened up a whole new world to us and elevated decision-making to a whole new level. Today, data is sliced, diced, and scrutinised to make informed decisions. Will this analysis be useful if we ignore the business aspect of the problem at hand? No. Data Analytics Consulting Services is a functional role that aims to deliver value-added analytical solutions by balancing business and hardcore analytics.

Most analytics firms now provide clients with data science consulting services across various business domains such as telecommunications, financial services, retail, pharmaceuticals, consumer goods, and so on, emphasising the importance of thoroughly understanding and addressing business needs.

Why Is Artificial Intelligence and Data Science Important for Your Business?

It’s become common knowledge that modern businesses are inundated with data. Last year, it was McKinsey who estimated that big data initiatives in the US healthcare system “could account for $300 billion to $450 billion in reduced healthcare spending or 12 to 17 per cent of the $2.6 trillion baselines in US healthcare costs”. On the other hand, bad data is estimated to cost the United States $3.1 trillion per year.
The advantages of AI adoption in business are numerous. 54% of business executives believe AI tools have increased productivity

What Exactly is Business Analytics?

The demand for business analytics professionals is increasing as Big Data grows. A flood of abstract information exists, fueled by the internet over two decades ago and accelerating at a much faster rate in recent years. 

Long-used database management and analysis techniques are no longer adequate, especially when dealing with unstructured data such as product reviews and social media posts. Data analysis careers—including business analytics, business intelligence, and data science positions new methods for organising, gaining insights from, and making predictions from this ever-increasing amount of data, and frequently incorporate computer science and other technical knowledge.

You may be wondering, “What is business analytics?” if you’ve spent the last few decades in an analytical role or if you’re exploring the myriad of computer science applications. Here’s an introduction to this burgeoning field and the skills required to get started.

What Role Does Data Analytics Play in Business Decisions?

According to a 2020 NewVantage Partners report, 64.8% of Fortune 1000 companies surveyed have invested at least $50 million in their business analytics efforts, with 91.5% attempting to implement AI-based technologies in some form. While these figures appear to show progress, the fact is that only 14.6% of all responding businesses used these technologies in their operations.

Aside from the technologies and capabilities themselves, the ability to make accurate decisions based on facts and past performance remains at the heart of business analytics. Decisions based on gut instinct (or, until about a decade ago, limited data) result in costly investments, whether in terms of money or the hours put into developing new initiatives that fail.

The insights gained within this general framework ultimately help optimise and streamline business processes, eliminating any estimates and grey areas in the process. Thus, organizational-wide optimization could include:

• Shaping and assessing future company decisions based on the success of previous initiatives or market trends;
• Examining and influencing the performance of individual departments within an organisation;
• Monitoring employee productivity and performance;
• Determining current and future staffing requirements, as well as the market skills required to effectively perform these roles;
• Evaluating and forecasting the performance of potential investments
• Determining the demand for a specific product or service based on market trends and consumer behaviour
• Scheduling the release of new products and media;
• Analysing product sales by location and using that data to meet future customer demands;
• Establishing optimal logistics routes for shipping and delivering goods;
• Making product recommendations based on previous search habits of customers;
• Data collection from vehicles and equipment in order to improve future performance and
• Identifying potential growth opportunities for a business, and how these scenarios could play out.