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Big Data for Beginners: A Technical Guide

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Big Data has become a popular buzzword in the technology industry, and for good reason. Companies are leveraging massive data sets to improve decision-making, enhance customer experiences, and drive innovation. But for beginners, the world of Big Data can be daunting. This technical guide aims to break down the basics of Big Data, from understanding data structures to processing real-time data with Spark.

Introduction to Big Data

Big Data refers to extremely large sets of structured, unstructured, and semi-structured data that are too complex to be processed by traditional data processing software. This data can come from a variety of sources, including social media, sensors, websites, and more. The three key characteristics of Big Data are volume, velocity, and variety.

Understanding Data Structures

Data structures are the way data is organized and stored. Big Data can be structured, semi-structured, or unstructured. Structured data has a defined schema, whereas unstructured data does not. Semi-structured data is a combination of both. Common data structures include databases, spreadsheets, and XML files.

Data Mining and Analysis

Data mining is the process of extracting valuable insights from data. It involves using statistical and machine learning algorithms to identify patterns and relationships in data. Data analysis refers to the process of analyzing and interpreting data to make informed decisions based on the insights gained from data mining.

Managing Data with Hadoop

Hadoop is an open-source software framework that allows for the distributed storage and processing of large data sets across clusters of computers. It is a powerful tool for managing Big Data as it can store and process massive amounts of data in parallel, making it faster and more efficient than traditional methods.

Processing Big Data with Spark

Spark is another open-source software framework that is used for processing Big Data. It is designed to be faster than Hadoop and can run workloads up to 100x faster in memory and 10x faster on disk. Spark is highly scalable and can be used for both batch processing and real-time streaming.

Real-time Data Processing

Real-time data processing refers to the ability to process data as it is generated, rather than after it has been collected. This is important for applications that require immediate insights or actions, such as fraud detection or real-time recommendations. Technologies such as Apache Kafka and Apache Flink are commonly used for real-time data processing.

NoSQL Databases: An Overview

NoSQL databases are non-relational databases that are used for managing Big Data. They offer more flexible data models than traditional relational databases and are highly scalable. Common types of NoSQL databases include document, key-value, column-family, and graph databases.

Data Security and Privacy

Data security and privacy are critical components of Big Data processing. Companies must ensure that sensitive data is protected from unauthorized access or breaches. This involves implementing security measures such as encryption, access controls, and firewalls.

Challenges in Big Data Processing

Big Data processing poses several challenges, including data quality, scalability, and interoperability. Ensuring that data is of high quality and can be easily integrated with other data sources is critical for successful Big Data processing. Additionally, as data volumes grow, scalability becomes increasingly important.

The Future of Big Data Technology

The future of Big Data technology looks promising. As data volumes continue to grow, new technologies and tools are emerging to help companies manage and process Big Data more efficiently. Machine learning and artificial intelligence are also being integrated into Big Data processing, allowing for better insights and decision-making. In conclusion, Big Data offers a wealth of opportunities for companies to improve their operations and drive innovation. However, successful Big Data processing requires a sound understanding of data structures, data mining, analysis, and processing technologies. By following best practices for data security and privacy and addressing challenges such as scalability and interoperability, companies can leverage Big Data to gain a competitive advantage in their industry. Looking for more technical advice? Check out our other blogs under Tech Brew. Looking for True Tech Advisors? We are here to provide simple solutions to complex problems. We want to be your partner. Whether you need short-term advice, help with hiring, or want to establish a long-term relationship with a trusted partner, we’re here for you. You’re the best at what you do, and so are we. Together we can accomplish more. Contact us here

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Liana Blatnik

Director of Operations

Liana is a process-driven operations leader with nine years of experience in project management, technology program management, and business operations. She specializes in developing, scaling, and codifying workflows that drive efficiency, improve collaboration, and support long-term growth. Her expertise spans edtech, digital marketing solutions, and technology-driven initiatives, where she has played a key role in optimizing organizational processes and ensuring seamless execution.

With a keen eye for scalability and documentation, Liana has led initiatives that transform complex workflows into structured, repeatable, and efficient systems. She is passionate about creating well-documented frameworks that empower teams to work smarter, not harder—ensuring that operations run smoothly, even in fast-evolving environments.

Liana holds a Master of Science in Organizational Leadership with concentrations in Technology Management and Project Management from the University of Denver, as well as a Bachelor of Science from the United States Military Academy. Her strategic mindset and ability to bridge technology, operations, and leadership make her a driving force in operational excellence at VeriTech Consulting.

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Keri Fischer

CEO & Founder

Founder & CEO | Cybersecurity & Data Analytics Expert | SIGINT & OSINT Specialist

Keri Fischer is a highly accomplished cybersecurity, data science, and intelligence expert with over 20 years of experience in Signals Intelligence (SIGINT), Open Source Intelligence (OSINT), and cyberspace operations. A proven leader and strategist, Keri has played a pivotal role in advancing big data analytics, cyber defense, and intelligence integration within the U.S. Army Cyber Command (ARCYBER) and beyond.

As the Founder & CEO of VeriTech Consulting, Keri leverages extensive expertise in cloud computing, data analytics, DevOps, and secure cyber solutions to provide mission-critical guidance to government and defense organizations. She is also the Co-Founder of Code of Entry, a company dedicated to innovation in cybersecurity and intelligence.

Key Expertise & Accomplishments:

✅ Cyber & Intelligence Leadership – Served as a Senior Technician at ARCYBER’s Technical Warfare Center, providing SME support on big data, OSINT, and SIGINT policies and TTPs, shaping future Army cyber operations.
✅ Big Data & Advanced Analytics – Spearheaded ARCYBER’s Big Data Platform, enhancing cyber operations and intelligence fusion through cutting-edge data analytics.
✅ Cybersecurity & Risk Mitigation – Excelled in identifying, assessing, and mitigating security vulnerabilities, ensuring mission-critical systems remain secure, scalable, and resilient.
✅ Strategic Operations & Decision Support – Provided key intelligence support to Joint Force Headquarters-Cyber (JFHQ-C), Army Cyber Operations and Integration Center, and Theater Cyber Centers.
✅ Education & Innovation – The first-ever 170A to graduate from George Mason University’s Data Analytics Engineering Master’s program, setting a new standard for data-driven military cyber operations.

Career Highlights:

🔹 Senior Data Scientist – Led groundbreaking all domain efforts in analytics, machine learning, and data-driven operational solutions.
🔹 Senior Technician, U.S. Army Cyber Command (ARCYBER) – Recognized as the #1 warrant officer in the command, driving big data analytics and cyber intelligence strategies.
🔹 Division Chief, G2 Single Source Element, ARCYBER – Directed 20+ analysts in SIGINT, OSINT, and cyber intelligence, influencing Army cyber policies and operational training.
🔹 Senior Intelligence Analyst, ARCYBER – Built the Army’s first OSINT training program, improving intelligence support for cyberspace operations.

Recognition & Leadership:

🛡️ Lauded as “the foremost expert in data analytics in the Army” by senior leadership.
📌 Key advisor to the ARCYBER Commanding General on all data science matters.
🚀 Led the development of ARCYBER’s first-ever OSINT program and cyber intelligence initiatives.

Keri Fischer is a visionary in cybersecurity, intelligence, and data science, continuously pushing the boundaries of technological innovation in defense and national security. Through her leadership at VeriTech Consulting, she remains dedicated to helping organizations navigate the complexities of emerging technologies and drive mission success in an evolving cyber landscape.

Education:

National Intelligence University Graphic

National Intelligence University

Master of Science – MS Strategic Intelligence

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George Mason University Graphic

George Mason University

Master of Science – MS Data Analytics

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