Big Data Services
100+
Satisfied and Happy Clients we have Served all over the World.
What We Do
Evolve Your Business While Evolving Your Data Landscape as you Hire Big Data Consultants
The increasing volume of data & its complexity can be simplified with Tableau – a BI and visual data analytics suite, to help Businesses & people make informed decisions. Big Data with us for data management, insightful analysis, & effective visual presentation that are fast, convenient, & result-oriented to establish a Data Culture & spur change. With our Tableau developers, turn your data insights into value-based actions.
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Our Big Data Services
Big data consulting
You will get assistance for end-to-end big data solution implementation or for separate stages of your IT initiative. You can count on us to deliver a business case (e.g., to verify solution feasibility, create a competition strategy), estimate costs and ROI, design an architecture and recommend an optimal tech stack. We also provide consulting on achieving full security and regulatory compliance and implementing ML/AI-powered capabilities.
Big data implementation
You will get a system that automatically scales up and down depending on the load, smoothly fits your existing infrastructure, and is easy to upgrade in the future. We will choose techs that will enable the required performance at an optimal price. For highly complex cases, we can start with a Proof of Concept (PoC) or an MVP. This way, you can make sure of the solution’s feasibility and interact with an intermediate version of the software, provide your feedback, and thus let us adjust the system early on.
Improvement of a big data solution
You can turn to us to fix software inefficiencies or expand it with new capabilities. Our team will audit your system and introduce the required changes or provide you with actionable recommendations on their implementation. E.g., we can customize and configure big data infrastructure techs (like Hadoop, Kafka, Spark, NiFi, Cassandra, and MongoDB) and modernize data processing pipelines to improve solution performance, add/upgrade data encryption mechanisms to eliminate security vulnerabilities, enhance containerization to improve scalability, and more.
Support and maintenance of a big data solution
We can provide you with infrastructure support, solution administration, data cleansing, and other required support and maintenance services. Depending on your choice, you can request either one-time assistance or have our team to continuously monitor your software and fix and prevent issues.
See How Big Data Can be Used in Your Industry
Healthcare
- Healthcare data analytics with insigths into patient and financial management, treatment processes and outcomes, laboratory management, and more.
- Remote patient monitoring.
- Smart medical devices and hospital asset tracking.
- Recommendations on care personalization.
- Data analytics for clinical trials.
Manufacturing
- Manufacturing data analytics with insights into OEE and production optimization, quality control management.
- Real-time equipment monitoring and predictive maintenance.
- Real-time asset tracking.
- SCM and fleet management analysis.
Banking
- Banking analytics with continuous monitoring of an institution’s stability indicators, operational and marketing management insights, and more.
- ML/AI-powered recommendations for customer service personalization.
- Continuous market monitoring, what-if modeling, and forecasting.
- Transactions monitoring with alerting on risk-incurring events (e.g., identity theft, money-laundering activity).
Lending
- Lending analytics to provide insights into loan underwriting, loan servicing, and portfolio performance.
- Borrower creditworthiness evaluation.
- AI-powered planning and execution of debt collection.
- Loan demand and profitability forecasts.
- Real-time tracking of portfolio transactions.
- Lending fraud detection and alerting.
Investment
- Investment analytics to track portfolio performance, get insights into operational processes, and more.
- Financial returns forecasts.
- ML/AI-driven stock buying recommendations and investment prescriptions.
- Continuous monitoring of market, liquidity, and credit risks.
- Identification of pump and dump schemes, insider trading, HFT manipulation, and other investment fraud.
Insurance
- Insurance analytics to provide insights into sales, customer, claim, and finance management.
- Insurance automation, including claim processing and underwriting.
- Predictions of insurance events and what-if modeling for the required business processes.
- ML/AI-powered prescriptions (e.g., on claim denial or approval, optimal insurance prices).
- Detection of fraudulent transactions and their automated blocking.
Our Big Data Customers Are Also Interested In
devstudio360 combines big data expertise with decades-long experience in software engineering and other advanced technologies to deliver end-to-end big data applications that bring maximum value to their users.
Machine learning
Building highly accurate ML models that identify hidden patterns in big data, provide reliable forecasts, power complex neural networks, and automate complex business algorithms.
Artificial intelligence
Developing personalization engines, natural language processing systems, computer vision, and other AI-powered solutions that maintain stable performance under any data load.
Data science
Providing strategic and technological guidance in wrangling, exploring, and applying data, we employ reliable statistical methods, establish robust data quality management processes, and help avoid issues related to inaccurate data and false predictions.
Business intelligence
Integrating large volumes of high-velocity data into scalable, fault-tolerant analytics solutions that provide trustworthy insights to any number of users.
Data visualization
Creating easy-to-navigate, customizable reports and dashboards that are tailored to the needs of specific business users and provide a clear and concentrated view of data insights that matter most.
Cloud services
Proficient in Azure, AWS, and GCP, we build cloud big data solutions from scratch and migrate legacy workloads to the cloud to achieve better scalability, cost-efficiency, and availability of our clients’ data.
Frequently Asked Questions
How much does big data implementation cost?
Big data implementation costs may vary from $200,000 to $3,000,000 for a mid-sized organization. The pricing depends on such factors as the number of data sources, data volume and complexity, data processing specifics (batch, real-time, or both), requirements for security and compliance, deployment model.
What are the types of big data?
There are three main types of big data:
- Structured data: it can be easily organized in tables, e.g., customer demographics data, financial transactions, and sales. Such data is easy to sort for further queries via BI tools.
- Unstructured data can’t be organized into any logical structure until it is processed with complex technologies like AI, ML, natural language processing (NLP), and optical character recognition (OCR). The examples of unstructured data include texts, images, videos, and audio recordings. E.g., a company can apply NLP to customer social media posts to understand the sentiment towards the service.
- Semi-structured data is in between the two previous types. On the one hand, its elements can be assigned to certain fields or tags, but on the other hand, these elements are not always ready for querying or analytics. An example of semi-structured data can be an email with a subject line and a message body, where the line and the text will go to the correspondingly tagged fields and later be processed with techniques required for unstructured data.
What are the sources of big data?
Internal big data sources: customer-facing apps, ecommerce platforms, enterprise systems like CRM, ERP, EHR.
External big data sources: data from stock exchanges, banks, and credit companies, weather-forecasting services, online marketplaces, web tracking tools, GPS systems and traffic cameras, social media platforms, etc.
