Big data and advanced analytics, Poradniki, Projekty, Badania z Big data

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Big Data and Advanced Analytics

for Strategic Decision-Making

Marta Dorenda

AGENDA

1. Big Data – what is it all about?

2. Decision Making Processes

3. Benefits of Big Data Analytics

4. What can go wrong?

2.5 quintillion bytes of data generated daily (one

quintillion is a 1 followed by 18 zeros!)

global big data analytics market is worth $

billion and

expected to reach $425.9 billion by 2025

The evolution of big data in business

strategy

K ey market trends :

exponential growth of Internet of Things (IoT) increasing reliance on cloud computing. business intelligence transceded to offer predictive and prescriptive analytics.

First V: Volume

• sheer amount of data generated and collected. Anything from structured data (like numbers and dates) to unstructured data (like text, images, and videos);
• Major challenge for organizations. How do we store it all? How do we process it? How do we make sense of it?
• Specialized tools and technologies capable of handling massive amounts of data. Technologies: Hadoop, Spark and NoSQL databases come in;
• Scalable, fault-tolerant, and capable of processing data in parallel across multiple nodes tools;

Second V: Velocity

• speed at which data is generated, processed, and analyzed;
  • processing in real time is crucial for businesses - quick decisions (financial institutions, e-commerce companies);
• to handle high-velocity data, businesses need to invest in technologies that can process and analyze data quickly

Fourth V: Veracity

• accuracy and trustworthness of the data;
  • data governance (policies, procedures, controls);
  • data profiling, data cleansing, data validation, and data auditing.

Fifth V: Value

• valuable insights and create value for businesses and organizations;
• improving decision-making processes, creating new revenue streams, reducing costs, increasing operational efficiency, and enhancing customer experiences;
• reliable data sources, effective data management processes, and skilled data professionals

Enhancing Decision-Making Processes

Arguably the most crucial role of data analytics in a business strategy is its

ability to enhance the decision-making process. By providing valuable

insights into business operations, customer behavior, and market trends,

data analytics allows businesses to make decisions grounded in hard data

rather than intuition or assumption. This process significantly reduces risk

and increases the likelihood of a successful outcome.

Practical applications of big data across industries

• Transportation : GPS applications – optimized route planning; aviation analytics process - fuel efficiency and safety;
• Healthcare : wearable, embedded sensors – collection of valuable patient data in real-time;
• Banking and Financial Services : monitoring of purchase behavioral pattern of credit cardholders - potential fraud detection; risk management and customer relationship management optimization;
• Government : tax fraud identification; tracking the spread of infectious diseases;
• Media and entertainment : companies like Amazon and Spotify use big data analytics to recommend personalized content to users. Additionally, big data aids in personalized marketing with companies like Amazon using customer data to tailor marketing strategies, leading to more effective ad placements.

IDENTIFYING CUSTOMER TRENDS AND BEHAVIOURS STREAMLINING OPERATIONS ASSESSING AND MANAGING RISKS DRIVING INNOVATION ENABLING PREDICTIVE ANALYTICS

Benefits of Big Data Analytics faster, more informed decision making cost reduction and operational efficiency enhanced data-driven go-to-market strategies

How to act?

1. The Future of Data Science in Business
   2. Cultivating a Data- Driven Culture
2. Upskilling and Improving of Abilities
3. Empowering Decision-Makers through Data Science
4. Fostering Innovation through Data Science

Big data predictions and preparations In the next decade, big data is set to undergo significant transformations, driven by advancements in AI and machine learning. Forecasts suggest the global data sphere will reach 175 zettabytes by 2025 (175 trillion USB sticks with a 1GB capacity), underscoring the growing volume and complexity of data. To stay ahead, businesses must invest in scalable data infrastructure and enhance their workforce's analytical skills. Adapting to emerging data privacy regulations and maintaining robust data governance will also be vital. With this proactive approach, businesses will be set to successfully utilize big data, ensuring continued innovation and competitiveness in a data-centric future.