As per a McKinsey report, most businesses simply talk about data analysis and do little else for its actual implementation. McKinsey conducted an analysis on five major business sectors to find out what’s lacking. In most cases, companies have not been able to scale up the experiments they carried out at smaller scale to reap the full benefits of data analytics. According to Gartner, companies do not understand big data fully and don’t ask the correct questions to reap the potential benefits.
The only sectors that seem to be utilising big data productively are retail and location-based services. Most of the other sectors such as manufacturing, public sector companies, and healthcare haven’t yet understood the potential of data analytics. Moreover, as new opportunities come up, the gap between those who are leading and those who are lagging behind is becoming bigger.
Barriers to Big Data adoption
Culture, mindset patterns and organizational structure create the biggest hurdles in the adoption of big data and analytics. Businesses are still not able to adapt the key processes and create scalable solutions. This requires not just the adoption of tactic but a change in mind-set to make necessary changes in the company’s business model.
The next big challenge is to find and retain experts and data scientists. As such, there is a lack of such professionals in the market. Most data scientists, with the capability of modelling data, work with organizations such as CERN where there are huge amounts of data. Hence, there is a gap in the market for professionals trained in big data analytics. Institutions and IT giants must look at this as an opportunity to create a pool of data scientists by providing advanced data science and analytics courses.
Another problem is people who call themselves data scientists may not actually be so.
Hence, when hiring, the HR managers must make sure that those who promote themselves as data scientists are actually fit for the tag. As such, there is a need for data scientists with business acumen so that they can relate and solve business problems with data solutions. The specific term for such talent is “business translators.” As per the McKinsey study, the demand for such talent will be between 2 to 4 million in the United States alone over the period of the next ten years.
As of now machine learning and AI are still in initial stages and not part of mainstream business. As their use proliferates the market, data analytics would rapidly bring changes to business models. Organizations must, therefore, invest in learning how to harness the power of data analytics and big data to their full potential lest they risk losing out to competition in future.
What is Marketing Data Analysis?
Marketing data analysis is a technique used by businesses to gather all available information regarding the market and come up with an effective marketing plan. It is a very critical piece for building an effective marketing strategy for any sort of business. It also shows you how well you have done in the market with your current marketing techniques and what all you need to do to improve your marketing strategy.
In order to understand the importance of data analytics certification online, first, you need to understand the importance of market research and data analytics. So, let’s get to it.
Importance of Market Research & Data Analytics
When you are an investor or an entrepreneur, you need to know what you are getting yourself into. In order to do that, you need to have all the data to back up your goal or vision for the company. And for that, you need to perform market research and data analysis. Here are the top 3 reasons why market research and data analysis is important for any organization.
- Reports of the Past
By analyzing the past performance of the business, you get to know which project performed better than others and which technique worked and which didn’t. This way you avoid making the same mistakes over and over and can change the course of action.
- Analyzing the Current Market
Market research & data analytics allow you to understand the current market better. It enables you to understand which methods are working and trending. It also answers questions like how the customers are responding to your marketing plan and answers what improvements you can implement to perform better.
- Predicting the Future
Market research and data analysis helps you get an idea regarding the future. It looks into trends and growths in the current market and forecasts the companies’ future based on that. This, in turn, allows the company to set marketing plans for the future.
Why Market Research & Data Analytics Course from Talentedge?
- Live & Interactive Digital Learning
The online data analytics course by Talentedge offers live and interactive digital learning that empowers the learners to receive par excellence from anywhere at any time. The data analytics certification online focuses on building a strong foundation in market research and data analytics for entry-level to mid-level professionals.
- Convenient Class Schedule
Talentedge offers the professionals convenience to schedule classes at their own comfortable timings. Along with this, professionals familiarize themselves with core and important concepts applied in data analytics like machine learning and perspective analysis.
- One-on-one Interactions
The data analytics certification online from Talentedge comes with one on one interactions and all the classes are delivered live by eminent faculty encouraging interactive discussions and query resolution.
An online market research & data analytics course from Talentedge provides professionals with an overview to develop strategies based on the findings from the data, to manage the organization. It creates a working knowledge of the research industry, the role of market research and data analytics, and its relationship to strategy building. To top it all off, Talentedge partners up with top Indian and international institutes including IIMs, XLRI, MICA, SPJIMR, and many others to provide the best-in-class digital learning experience.