Data analytics services is a business term for the process of inspecting, cleansing, transforming and modeling data with the intent of discovering useful information, suggesting conclusions and supporting decision-making. The term is sometimes used interchangeably with business intelligence, although data analytics implies greater rigor and focus on statistics and machine learning. The goal of data analytics is to improve decision quality by taking advantage of modern big data capabilities.
The need for businesses to employ data analytics company has arisen due to the vast growth in digital data over recent years. This explosion of data arises from several sources: the increasing number of online transactions; the proliferation of mobile devices and sensors that generate large volumes of sensor data (“Internet Things”); the rise of social media and web-based information sharing; and many other sources. In addition, data volumes are growing at a very fast rate – at least doubling every year.
Data analytics services providers allows organizations to make better business decisions by identifying patterns within the data, determining correlations between datasets, and predicting future trends or behavior. There are different types of analysis for different types of data: social media content analysis may be used to predict market conditions based on consumer opinions posted online; mobile phone location tracking can suggest debtors who have moved without paying their loans; vehicle telematics can identify risky driving behaviors such as extreme speeding.
5 types of data analytic services
1. Descriptive Analytics-
It is more focused on summarizing data, to make it easier for humans to understand what has happened. It also forecasts future trends. One of the most common examples of this type is market research reports which tend to focus on understanding customer behavior and trying to predict future consumer behavior patterns. The goal is not really to understand why customers behave the way they do but rather just find out what they are doing without delving into explanations for their actions.
2. Diagnostic Analytics-
Diagnostic analytics are used for problem solving, root cause analysis or process optimization, especially in manufacturing environments where products can be built on high volumes at low costs to automation processes. To accomplish these tasks, it is necessary to have good data about the as-is process and also about the desired or ideal state. The goal of diagnostic analytics is to identify gaps between the as-is and to-be states so that process improvements can be identified and made.
3. Predictive Analytics-
This type of analytics makes predictions by applying past data to mathematical models. This helps organizations answer important business questions such as what are the chances that a particular customer will default on a loan, how many units of a product needs to be produced to achieve certain sales targets or what is the likelihood of a natural disaster happening in a particular area. Predictive analytics often makes use of machine learning techniques to build models that are able to learn from past data and make predictions.
4. Prescriptive Analytics-
It helps organizations to take advantage of the insights derived from other types of analytics, especially predictive analytics for process optimization and decision making. It combines what-if analysis with simulation-based models to explore different scenarios against which business decisions can be made. For example, an organization may use simulations to forecast how likely it is that a particular product will sell or what are the chances that a project might overshoot its budget if certain changes are made. This type of analytics also uses optimization techniques to find Pareto optimal solutions that work best across all constraints.
5. Optimization Analytics-
Optimization Analytics is used to maximize efficiency by using machine learning techniques for solving complex resource allocation problems. This type of analytics is commonly used by transportation companies, telecom providers, energy providers and other large-scale businesses to optimize their networks or resources. It can also be used for solving complex real-world problems in finance, healthcare and other domains.
Do businesses need data analytics services?
1. Improved decision making – Better decisions can be made by understanding patterns within the data, determining correlations between datasets and predicting future trends or behavior.
2. Enhanced customer insights – Insights into customer behavior can be gleaned from social media content analysis, mobile phone location tracking, vehicle telematics and other sources of data. This helps organizations to better understand what customers want and need and how they might respond to new offers or products.
3. Greater operational efficiency – By understanding how resources are used and where bottlenecks occur, businesses can optimize their operations for greater efficiency.
4. Improved risk management – analytics can help organizations to identify potential risks and take steps to mitigate them. This might include fraud detection, identifying areas of vulnerability and assessing the impact of possible threats.
5. Competitive advantage – Organizations that make use of data analytics stand a better chance of outperforming their competitors who do not have the same level of insights into customer behavior, patterns in sales and other aspects of business performance.
What is trending in data analytics?
1. The use of artificial intelligence (AI) and machine learning for predictive and prescriptive analytics.
2. The increasing use of big data techniques to process large volumes of data for insights.
3. The growing popularity of data visualization tools for understanding complex datasets.
4. The emergence of blockchain technology and its potential use in the area of data analytics.
5. The increasing demand for skilled data scientists and analysts who can make sense of all the data that is now available.
How much do data analytics companies charge?
Prices for data analytics services can vary considerably depending on the size and complexity of the project. However, most companies charge a per-hour or per-day rate for their services. Some also charge a monthly retainer fee to continue providing support and updates to the analytics software once it has been implemented.
It is clear that businesses need data analytics services if they want to make the most of the data they have available. By understanding customer behavior, predicting future trends and making better decisions, businesses can achieve a competitive advantage and improve their performance. Data analytics companies can help businesses to get started with data analytics and make the most of the insights it provides.
What do data analytics consultants do?
1. Data Analytics Consultants use big data to provide insights into customer behavior and recommend ways to improve business performance. They might also develop new products or services that better meet the needs of customers.
2. Data Analytics Consultants work with a range of software tools, such as predictive analytics, decision support systems and prescriptive analytics platforms for identifying patterns in large datasets and many different types of data sources including mobile phone records, location tracking information from mobile devices and other consumer electronics, social network comments and other online content, supply chain transactions and financial records. This helps companies make sense of all their resources in order to maximize efficiency and boost performance.
3. It is common for businesses to outsource data analysis projects because they are time-consuming and complex. Data Analytics Consultants are often brought in to work on such projects. They have the skills to quickly understand the data, develop models and create reports that present findings in a way that is easy for business executives to understand.
How ZrTech can Help?
ZrTech is a data analytics company that can help you make the most of your data. We have a team of experienced data scientists and analysts who can work with you to understand your data and develop models and insights that will help you improve your business performance. We also use the latest software tools and techniques to provide you with actionable insights for your business.