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Our Big Data services already power over 200 active engagements. We typically land our teams within 2 weeks, so you can start shipping top quality software, fast.
“Their engineers perform at very high standards. We've had a strong relationship for almost 7 years.”
From business intelligence and ETL pipelines to platform development, storage, visualization, and AI-driven analytics—we deliver big data solutions aligned with your data architecture and business goals.
Find opportunities, mitigate risks and optimize performance in real-time. Our big data scientists create custom analytics solutions that can extract insights from huge datasets as they are being generated.
For your analytics stack, we use Power BI and Tableau for visualization, Apache Spark for real-time processing, and TensorFlow and Scikit-learn for machine learning. For scalable data warehousing, we use Snowflake and Google BigQuery.
Turn disparate data sources into one unified, high-quality dataset—even in the most complex data environments. Our integration and ETL solutions give you data that's consistent, accurate and ready for real-time insights. So you can eliminate inefficiencies and speed up decision-making.
We use Apache NiFi and Talend for seamless extraction, transformation and loading (ETL). Our experts use Airflow and dbt for complex workflow orchestration. We also use Amazon Redshift and Azure Synapse for querying in our data warehousing solutions.
Struggling to make sense of data spread across multiple platforms? We specialize in capturing, collecting and moving massive amounts of structured and unstructured data from real-time streams, databases or third-party APIs into your data architecture.
Our experts use Apache Kafka and AWS Kinesis for real-time streaming ingestion, Apache Flume for log data aggregation and Google Cloud Dataflow for both batch and stream processing. With these tools we build fast and scalable data pipelines that power timely insights and informed decisions.
Process, store and analyze huge amounts of data at high speed and efficiency. Whether you need to power predictive modeling, advanced data analytics or AI-driven applications, we architect platforms that can handle real-time analytics to large-scale batch processing.
Our developers use Hadoop and Apache Spark to build scalable, distributed systems and integrate HDFS, Amazon S3 and Google Cloud Storage for secure, high-throughput data storage. For querying we use Presto for fast ad-hoc querying and Apache Hive for large-scale batch queries. Our experts also use Docker and Kubernetes for agile, optimized performance.
Support real-time data streams, large-scale archives and high-speed transactions. We design and implement scalable storage systems that can handle huge amounts of structured and unstructured data. Our solutions store it securely, retrieve it quickly and manage it with minimal downtime or errors.
Our experts use technologies like Amazon S3, Google Cloud Storage and HDFS for distributed storage, for durability and fault tolerance. We also implement advanced data replication and backup strategies using tools like Apache Cassandra for distributed NoSQL databases and PostgreSQL for relational databases.
Turn complex datasets into clear, actionable insights. We specialize in converting raw data into interactive, easy-to-understand visualizations. Whether you want to track performance metrics, identify market trends or uncover hidden patterns our visualizations help you make faster, data-driven decisions.
We use leading tools like Tableau, Power BI and D3.js to create dynamic dashboards, charts and graphs. With just a few clicks you can drill down into details or view high-level summaries. By integrating real-time data streams our visualizations are always up to date.
Get intelligent systems that process massive datasets and learn from them. Our AI-driven solutions deliver actionable insights that allow you to automate routine processes, forecast market trends and even build recommendation engines.
We use powerful frameworks like TensorFlow, PyTorch and Scikit-learn to develop machine-learning models. Our data scientists then use them to extract patterns, build predictive algorithms and automate decision-making processes. Our expertise also includes tools like Google AI and AWS SageMaker for scalable model training, deployment and continuous monitoring.
Big data is transforming many industries by providing insights, improving decision-making and innovation. Here are the key industries where our big data solutions make the most impact:
Healthcare: to optimize patient care, predictive analytics, drug discovery, personalized medicine
Finance and Banking: to detect fraud, manage risk, personalize financial products, algorithmic trading, regulatory compliance
Retail and E-commerce: to analyze customer behavior, recommend products, inventory management, personalize marketing
Telecommunications: to optimize networks, customer churn prediction, customer service through real-time data analysis
Manufacturing: to optimize supply chain, improve production processes, predict equipment failure through sensor data
Government and Public Sector: to inform policy, urban planning, public safety
Energy and Utilities: to analyze energy consumption, grid management, operational efficiency
Media and Entertainment: to personalize content recommendations, advertising strategies
Travel and Hospitality: to personalize customer experience, pricing strategies, guest experience
Automotive: to design vehicles, predictive maintenance, autonomous driving
Big data is transforming many industries by providing insights, improving decision-making and innovation. Organizations that invest in scalable data platforms gain faster answers from larger datasets, automate routine analysis, and uncover patterns that manual reporting cannot surface.
From predictive maintenance and fraud detection to personalized customer experiences, big data solutions turn raw information into actionable intelligence. When pipelines, storage, and governance are designed together, teams spend less time reconciling sources and more time acting on trusted insights.
We follow proven practices across infrastructure, security, and data quality so your big data platform stays flexible, compliant, and valuable as volumes grow.
Your platform should be designed to handle growing data and emerging technologies like AI. Here's how we build flexible, scalable data platforms that allow our clients to adapt to new demands without hitting performance bottlenecks:
01
We use streaming technologies like Apache Kafka or AWS Kinesis to ingest, process and analyze data in real time. This means you can make decisions based on the latest data.
02
We leverage cloud platforms like AWS, Google Cloud or Azure to scale storage and processing power as your data grows and implement cost management practices to avoid unexpected costs. This eliminates the need for expensive on-premise infrastructure and promotes efficiency as data grows.
03
To manage diverse datasets we use a hybrid approach with data lakes for unstructured data (e.g. Hadoop, Amazon S3) and warehouses for structured data (e.g. Snowflake, Google BigQuery). We also explore data lakehouse architectures which offer more flexibility and cost efficiency.
04
Our experts use tools like Docker and Kubernetes to build flexible, modular big data applications that can scale and adapt as business needs change.
With cyber threats on the rise and regulations getting stricter it's vital to protect your data and be compliant. We use advanced security practices to protect sensitive information and keep you compliant with global standards.
01
To protect sensitive information from breaches we ensure all data is encrypted at rest and in transit using standards like TLS and AES-256.
02
We recommend you limit access to data and systems based on the principle of least privilege, using multi-factor authentication and role-based access controls. This means only authorised users can access critical data.
03
We set up continuous monitoring of data access and usage. With tools like Splunk or Datadog we detect suspicious activity and prevent breaches before they happen.
04
We keep you up-to-date with regulations like GDPR, CCPA and industry specific standards (like HIPAA for healthcare) by conducting regular compliance audits and implementing automated data governance tools like Collibra or Talend. We also prioritise certifications like SOC 2 and ISO 27001 which are required for data security standards.
Data loses value if it's not accessible and understood across all teams. Our approach ensures data is reliable and easy for everyone to consume. So it can support faster, smarter decisions across your organisation.
01
Teams can't use what they can't understand. We give non-technical teams user-friendly BI tools like Tableau, Power BI or Looker so they can analyze and act on data insights without needing a data science team.
02
We use machine learning-driven data cleansing tools to identify and remove inaccuracies, duplicates or inconsistencies so only high quality data informs decision making. For extra precision we use tools like Trifacta and Apache NiFi which are designed for robust data cleansing and preparation.
03
We regularly measure the return on investment from big data initiatives by linking insights to measurable outcomes like increased revenue, cost savings or operational efficiency.
We bring together the top 1% of big data engineers and data scientists from LATAM. Our carefully vetted experts are proficient in leading big data tools like Hadoop, Spark, and Azure Data Lake. When you partner with us, you get a team of 4000+ devs with expertise in 130 industry sectors.
Based in LATAM, our nearshore developers work in US time zones. This workday alignment means you enjoy faster responses, real-time communication, and more efficient project delivery. Work with us and tackle big data science challenges with minimal delays and optimal productivity.
Companies have trusted us to deliver cutting-edge big data science solutions for over a decade. Our developers have deep expertise in managing vast datasets and implementing advanced analytics. Plus, we excel at using top-tier tools and platforms, from AWS Redshift to Google BigQuery.
How we work
During our first discussion, we'll delve into your business goals, budget, and timeline. This stage helps us gauge whether you'll need a dedicated software development team or one of our other engagement models (staff augmentation or end-to-end software outsourcing).
We'll formulate a detailed strategy that outlines our approach to big data development, aligned with your specific needs and chosen engagement model. Get a team of top 1% specialists working for you.
With the strategy in place and the team assembled, we'll commence work. As we navigate through the development phase, we commit to regularly updating you on the progress, keeping a close eye on vital metrics to ensure transparency and alignment with your goals.
Strengthen your delivery roadmap by pairing Big Data with adjacent services, industry expertise, and technology capabilities.
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