List of Leading Data Analytics Companies in the USA

One of the strongest attributes that companies employ in the modern world market is data analytics, which helps them accelerate their advancement, make more conscious decisions, and outrun their rivals. In different industries, organizations are seeking the services of specific data analytics companies to analyze huge volumes of data, extract useful information, and help them thrive in the digital era. This blog offers a complete list of the top data analytics companies in the USA, their strength, services, and why they are relied upon by big brands.

What is Data Analytics?

Data analytics comprises a process of analyzing raw data to identify trends, patterns, and insights that would aid organizations in arriving at competitive decisions. This implies the application of tools, software, and high-tech tools like artificial intelligence (AI), machine learning (ML), and big data platforms.

How Does Data Analytics Work?

Data analytics is an operation that employs a corresponding system and program that incorporates machine learning algorithms, automation, etc. This is done in the following steps:

• Data Acquisition: You should acquire data through different sources to analyze it according to your useful business questions with the help of some code, such as SQL or Python. These sources could be in the form of databases, files, or external feeds, user submissions, or even social media. In the meantime, the data could be unstructured or structured and have various formats.
• Data Preparation: You cannot use all the collected data to analyze it. Thus, you need to clean up and reorganize the data so that it will be possible to analyze. This includes handling lost or inconsistent data and joining various data sets into one uniform source of data.
• Data Exploration: The phase consists of the employment of statistical methods in order to derive valuable information from the data. In this way, analysts investigate the data with the aim of perceiving the structure and distribution of the information and detecting the outliers or anomalies.
• Data Modeling: It uses the modeling of mathematics on the data set in order to deduce patterns and relationships. These models could be descriptive, forecasting the past, predictive, forecasting the future, or prescriptive, which makes suggestions.
• Communication of Insights: The last step is visualizing the information and presenting the results in a manner that is comprehensible and able to be acted upon by the stakeholders. This can be either in the form of the preparation of dashboards, reports, or presentations.

4 Types of Data Analytics

Data analytics mainly consist of four broad domains each of which has its points of foci and application:

• Descriptive Analytics: The question that is answered by this type of analytics is translated in the following way: What happened? It deals with historical analysis to realize developments that have been affecting a business. Engaging in descriptive analytics, by way of example, a retail company may want to know how many sales it made last year, how many people came into its store, and what its best-selling products are.
• Diagnostic Analytics: This may come in handy to answer the question, -Why did it happen? It entails further analysis of data to investigate more using deeper data exploration and drill-downs to know the actual cause of a specific output. As an example, in case the sales of a company decreased last quarter, diagnostic analytics could be applied to learn the reasons behind this.
• Predictive Analytics: These analytics can address a certain inquiry: What could occur in the future? An example is the ability of predictive analytics to estimate a claim’s chances of being a fraud in an insurance company.
• Prescriptive Analytics: This kind of data analytics answers the question of what we should do by approaching it through simulation and optimization algorithms, which provide possible solutions to the question. Another example is that of an airline relying on prescriptive analytics to determine the prices of tickets; here, there is a conflict between the necessity to sell tickets and the ability to earn maximally.

All these types of data analytics contribute significantly to decisions made in business and often combine to give full insights. As an example, a data analytics firm can employ descriptive and diagnostic analytics to get to the position the firm has at the moment and subsequently employ predictive and prescriptive analytics to recommend what is possible to be done in the future.

Top 5 Data Analytics Companies in the USA

IBM

Among the veterans of technology, IBM is still one of the pioneers of advanced technologies. The company was established in 1911, and it has conducted its business in more than 171 countries; it has provided thousands of job opportunities to tech engineers. This giant has been the first prolific giver of patents the world knows and a world patent leader in the USA.

SQL programming language which forms one of the main tools in data science, happened to is an IBM product. The company also offers a complete set of commercial data science tools and solutions to companies, which help businesses gain fast AI-driven innovations.

Oracle

The other tech giant, Oracle, is among the list of companies that lead in data science in the US. Oracle is a top enterprise software solution provider or vendor with professional databases and software-related business applications. Its products are used by more than 20,486 firms, including Fortune 500 companies.

Oracle Corporation is a global company, presenting its services in 62 countries. It’s one of the flagship products, the Oracle database, is among the absolute leaders in the area of enterprise grid computing. Besides, the projects that the Oracle team deals with include advanced analytics and data integration, cloud computing, CRM, and ERM.

Sisense

Sisense is a well-established cloud-based analytics provider that offers its clients the most advanced innovations in determining ways through which its clients are able to derive beneficial insights into their data. Its technologies, like deep learning and natural language processing, enable the company to assist businesses in uncovering the hidden patterns in their data, which they could never access.

Sisense has solutions that are tailored to specific industries such as healthcare industries and retail industries. Its ready-to-use offerings are advanced data pipelines, consulting assistance, complex analytics, and many more. Sisense has alliances with Amazon, Snowflake, and Google.

Microsoft

A list of software giants cannot in any way be complete without Microsoft. Nevertheless, even though this mammoth is popular in consumer software, it has also introduced excellent data science projects. Therefore, Microsoft Digital can use machine learning, data science, as well as Azure AI to enhance the experience for employees and vendors.

Through the information processing process, Microsoft gets a clear idea of how people are using their products and services. Besides, Microsoft Azure is an industrial benchmark in cloud computing platforms. Cloud Azure is utilized by businesses and small-scale entities to support their cloud analytics, virtual computations, storage, and networking capacities.

Amazon

The giant in the retail business has branded itself as the leader in innovation. If we discuss cloud computing, AI, and even drones, Amazon has been leading the technological scene all these years. The company also has significant data scientists, and it utilizes machine learning in order to enhance its products and services.

Amazon has also produced a digital assistant, namely Alexa, that is programmed to understand language in a human form and act intelligently using machine learning algorithms. It has the world-leading cloud platform is AWS, which presents more than 200 services, with data processing being one of them. Contino’s 2020 research report states that an outrageous 64 percent of enterprises use the AWS platform.

What will be the difficulties of data-driven analysis?

Access to Data

Most companies have yet to utilize data daily on a cross-functional basis. Others use sluggish, outdated ways, and others lack sufficient quality data to operate on. Data is usually hard to collect due to budgetary restrictions and the unavailability of personnel.

Data quality

Good data is complete, accurate, and fair. Data in today’s businesses is obtained through various sources and thus poses the difficulty of managing and cleaning. The analysis is based on low-quality input and might be misleading and one-sided.

Skill Gaps

Getting qualified data specialists is becoming more difficult. The talent competition has become fierce, and most companies are unable to get the right talent. This has been recorded as the greatest future challenge facing about 73 percent of companies.

Undefined business value

Information initiatives have to align with actual business objectives in order to succeed. A significant number of companies fail to verify whether they use analytics that can support decision-making or ROI. Good tools can not produce useful results without alignment.

Conclusion

Information is the oil of the digital era, and a data analytics firm is an ideal companion that can enable your company to unearth hidden secrets of data. Incorporating data analytics is one of the secrets to gaining invaluable information that keeps your organization or fortune. Are you, therefore, willing to get data revolutionized? Enter the realm of analytics companies and find out your opportunities! Please visit our website, Artema Tech, for more information.

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