Top Big Data Analytics Companies

Big data definition refers to the vast volume of structured as well as unstructured data available. The quantity of data is so large that it becomes impossible to churn using conventional database and software techniques. In this age of digital advancements, data plays a crucial role in changing the landscape of business processes. With the unlimited availability of information concerning potential customers and their purchasing habits, companies require big data and business intelligence to essentially analyze the data and update their risk management practices to match the current scenarios.

Here are four significant ways big data assists businesses in achieving their goals.

1. Decision Making:

The principal advantage of employing Big Data Analytics is that it boosts the decision-making process prominently. Big data analytics companies gather all the available data and organize them aptly for their client to make well-informed decisions. Big data solutions include the assessment of several customer-centric factors such as market trends, client requirements, competitors' strategies, etc. promoting a sound decision-making process.

2. Innovation:

Big data analytics consulting companies help businesses in updating current products to accommodate the changing trends. Big data systems collect massive amounts of data, allowing businesses to identify and curate new and innovative products to fit their customer base. Rather than just relying on their instincts, enterprises can now assemble their customers' feedback and product reviews to modify their solutions and deliver what the customers want.

3. Targeted Marketing:

With each industry shifting towards providing customer-centric solutions, organizations must recognize the right target demographic and market their product accordingly. To achieve this, businesses require extensive data about customer patterns. These patterns can further help the service providers in presenting hyper-personalized experiences to their clients and ensuring customer loyalty. Big data analytics can also predict what related products the customers may like, allowing companies to plan their marketing tactics accordingly.

4. Competitive Edge:

The availability of a vast range of service providers can make it challenging for decision-makers to create a name for themselves in the market. Whether a business is well-established or relatively new, it needs comprehensive intelligence to scan the market and traverse it subsequently. Big data analytics solutions level the playing field for each participant, providing the upcoming players a chance to transcend their competitors.

By implementing big data solutions within their organization, businesses are more apt to identify potential threats. Big data management creates a  risk prediction model, significantly contributing to mitigating risks without investing extensively.

1. Identifying Trends and Risk Factors:

Big data companies aid businesses in distinguishing current and forthcoming trends amongst their consumers. Statistical analysis enables new companies to build detailed business strategies. At the same time, established corporations can identify alterations in the behavior of the users in the early stages, making it possible to influence the business in a new direction. Analytics delivered by big data companies can also pinpoint the factors that cause customers to abandon the product or brand, thereby helping to reduce and counter high attrition rates. 

2. Operational Risks:

There are several risks that a business has to traverse daily, which also include decisions on the business location, target market as well as targeted audience, employee retention, data management, etc. With an expert big data system, organizations can easily recognize the key risk indicators (KRIs). Big data services introduce dynamic processes to measure, analyze, and visualize these KRIs to determine the course of action. Big data analytics services grant businesses complete control of the data, allowing full automation of systems to reduce manual intercession. 

3. Recognizing Potential Fraud:

Whether companies are dealing with the personal data of their clients or financial transactions, the threat of being under attack from external sources is constant. Big data analytics companies offer solutions to cross-check a large amount of internal and external data quickly. This affords fast and accurate identification and reduces the chances of fraudulent activity. Besides, businesses can also identify risks and scams during audits and assess potential partners or vendors, thereby ensuring a successful association with other organizations without being deceived.

4. Financial Risk Management:

Big data analytics consulting companies establish a system in place that can effectively identify fraudulent financial actions such as attempts at money laundering, loan scams, etc. By locating suspicious issues rapidly, big data companies can help their clients avoid financial losses. Big data analytics produces statistics after carefully studying the market, business model, competitors, etc. to evaluate market risks and asset liability. This is especially beneficial for financial organizations dealing with upcoming enterprises in determining whether the investment will bring profit to each participating stakeholder.

Businesses must understand the different types of big data services available and how they are beneficial for their project before investing. Therefore, check out the five most notable big data services:

1. Data Analytics:

Data analytics is attributed to the process of analyzing raw information and uncovering patterns to obtain valuable insights using them. This data could either be historic or recently acquired. Data analytics employs algorithmic methods by using several datasets to drive conclusions. With data analytics, businesses can easily map customer requirements and boost sales. 

2. Data Science:

Data science deals with unstructured and structured data that the experts collect, segregate, and interpret. Data science firms hold authority in distinguishing and eliminating unusual, insignificant, and risky data to simplify the task of data analysis. Data science uses statistics, programming, problem-solving, and other such abilities to equip decision-makers with accurate information and empower them to make informed choices.

3. Data Mining:

Data mining refers to the process of extracting useful patterns from the large sets of data available. Its core focus is on establishing previously undiscovered relationships amongst the available information. However, for successful data mining results, a vast and diverse database is imperative. Relational databases, text mining, and web mining are the different types of data mining processes.

4. Data Warehousing:

Data warehousing is an essential section in managing data from heterogeneous sources. It serves as electronic storage of a substantial amount of data that is designed for analysis. Whether the accumulated data is structured or unstructured, it can be stored in the cloud data warehouse, and available to the user whenever summoned. It is ideal for decision-makers who rely on vast amounts of data.

5. Edge Computing:

Edge computing is a revolutionary method that brings data closer to the devices while safeguarding it from latency issues. It facilitates the data analysis at the source of the data instead of the centralized servers and systems. Edge computing also ensures additional data security as the information does not travel across the network.

1. Hadoop:

Hadoop is an open-source framework developed by Apache. It is an ideal big data tool to scale data operations from a single server to multiple servers due to its ability to process large volumes of data available across clusters of networks.

2. Qubole:

Qubole is a cloud data platform created by the combined venture of Facebook’s Big Data infrastructure and Apache Hive. It extends big data services at a reduced price compared to other big data tools. Qubole offers features like intuitive GUI, optimized hive, auto-scaling, etc.

3. HPCC:

HPCC is developed by LexisNexis Risk Solution employing HPCC (High-Performance Computing Cluster) systems. HPCC enhances scalability and performance since it is easy to learn, upgrade, and program. It simplifies data processing with features like data profiling, data cleansing, data management tools, etc.

In this era of technology, most organizations are incorporating big data platforms within their current business model. Their primary goal is to improve consumers’ experience in addition to better-targeted marketing, cost reduction, and enhancing the efficiency of existing products. The top industries revolutionizing their processes via big data are as follows:

1. Big Data in Healthcare:

The contribution of big data analytics ranks high in the advancement of the healthcare industry. Big data in healthcare, when combined with specialized equipment that tracks the vitals of the patients, can simplify diagnoses. Technologies such as wearable devices, disease mapping, predictive analytics, etc. can change the way patients are treated and can save countless lives. Big data analytics solutions with wearable devices allow comprehensive data collection and empower doctors with patients' information detailing their current as well as past medical history. As an example of big data in healthcare, Beth Israel Deaconess Medical Center (BIDMC) of Boston, collects data from millions of patients and uses evidence-based medicine to identify high-risk patients and significant diseases. 

2. Big Data in Banking:

The banking sector can highly benefit from big data solutions. Bank customers can easily track and assess transaction histories and analyze upcoming bills and payments. Moreover, banks can easily study the shift in the market by studying the years of information and investing funds in projects that are most likely to be successful. Big data companies provide solutions to the banks against scams by preventing identity thefts and identifying fraudulent patterns. Big data systems are also beneficial in preventing money laundering, loan scams, etc.

3. Big Data in Education:

In the education industry, one of the biggest challenges is to bring together the vast amount of information available and compartmentalize it. By integrating big data, institutes can monitor the student's progress by tracking student logs, the hours spent on the system, providing additional worksheets, etc. Moreover, big data can be used to optimize the effectiveness of the institute by analyzing the performance of the teachers and measuring it against the number of students to derive the right proportion. It is also a practical module to help students select the correct course by studying student demographics, aspirations, subject matter, and other such variables. The University of Tasmania is one of the best examples of big data as it has developed a specialized Learning and Management System to properly use the data.

4. Big Data in Retail:

Retailers must always comprehend what their customers need and when they need it to stay ahead of their competitors. Big data analytics ensure customer retention by providing the insights required to meet their expectations and keep them happy. Data analytics companies can help establishments create a personalized shopping experience for their clientele by studying their preferences and purchasing patterns. Big data management also optimizes operational tasks, facilitates timely analysis of inventory, identifies repeat customers, and offers loyalty programs, as well as forecast demands. Retailers can also figure out potential reasons for losing clients and work on bypassing such situations.

5. Big Data in Transportation:

GPS or Global Positioning System has simplified transportation across the world. Big data firms can collect huge amounts of data from these location-based systems to create a safe, on-time, and comfortable journey for travelers. Transportation companies can outline customer journeys and provide them with personalized information to manage travel time, find the connecting vehicle, etc. Passengers may aptly find alternate routes, real-time seat availability, etc. Big data can additionally be used for traffic control, route planning, tracking mileage, logistics, and many more. Cities across the world such as Dublin, Stockholm, Da Nang, etc. have implemented big data to manage traffic and congestion, exhibiting an example of big data in road management.

Enterprises need to primarily understand their business objectives and then select a big data analytics company that is capable of turning those objectives into concrete results. 

1. Scalability:

It is crucial to find big data firms with the capacity to scale their solutions based on the size of your project as well as the number of resources you require. Inquire the big data company whether they process sufficient technology and storage capacity that is capable of accommodating your projects as it grows.

2. Cost:

One of the chief benefits of big data analytics is that it substantially lowers the operational cost of the business by storing, maintaining, and analyzing data sets. However, if the cost of hiring a big data agency is more than your current expenses, then it might not be a profitable decision. Ask about all the services offered by data analytics companies and then assess your funds to shortlist the ideal company offering the big data solutions within your budget.

3. Security:

While hiring a big data firm, question them about their security policies. Inquire about how do data analytics companies ensure digital integrity and data authenticity? What is their plan of action against the potential threats of hacking or tampering? It is advisable to opt for an NDA to ensure that there is no leakage of data from the big data analytics consulting companies

4. References:

Customers must request testimonials for their existing and previous clients. This will permit you to gauge their expertise in the field as well as their quality in delivering big data solutions. Moreover, check out the recommendations offered by past clients attributed to the big data company by exploring independent review and rating platforms, such as GoodFirms, to receive accurate customer feedback. 

5. Accessibility:

Another vital factor in determining the right big data analytics partner is the accessibility of the big data analytics solution designed by the service provider. If the layout and usage of the big data platform are excessively complex for you and your staff, then it can be challenging to achieve the right application of the big data system. Also, watch out for a big data system that provides in detail reports complete with charts, graphs, and journey outlines.

Based on your project, you may additionally inquire about other features offered by the big data company such as data compression, restricted or authorized access to the information, easy setup, tag-less solutions, etc.

The main goal of GoodFirms is to help service seekers connect with the best big data analytics consulting companies available across the globe. The list, as mentioned above, includes a wide variety of data analytics companies capable of delivering the kind of big data solutions you require. These companies are evaluated based on three vital criteria viz. Quality, Reliability, and Ability. These criteria are further subdivided to demonstrate the market penetration of the enterprises, their portfolio, the reviews and feedback received from genuine clients as well as their system integration and business intelligence & big data analytics.

GoodFirms urges established and novel big data agencies to provide proof of their achievements to grab a spot in our 'Research’ section. By getting listed, companies enhance their chances of receiving quality leads and boosting conversions, as well as building a name for themselves in the industry.