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Preparing a database strategy for Big Data

Turning big data from a curse into a blessing for your organization requires a strategic approach – but just what are the database challenges and opportunities introduced by big data?

In this expert e-guide, find key insights and tactics to help you prepare a database strategy for big data, and learn about the potential value of massively parallel processing (MPP). Read on to learn more today.

These are also closely related to: "Advances in Data Warehouse Performance"

  • Top Data Lakes and Lakehouses providers compared

    When organizations are investigating a data warehouse, lake, or lakehouse for their data analytics strategy — the most important factor to double click on when selecting a vendor is the use case it can address for the business now and in the future. Also, evaluate which vendor will enable you to connect to the data source of your choice and how it best aligns with your existing and future data infrastructure.

    This new GigaOm Radar report examines 10 of the top data lake and lakehouse solutions and compares offerings to arm decision-makers with the information needed to select the best fit for their business and use case requirements.

  • Case study: How PayPal improved its fraud detection strategy

    As a leading online money transfer system, and like most banking services, PayPal experiences fraud challenges. To improve security and identify emerging threats in real-time, they realized they needed to process and analyze more data faster.

    However, scaling the amount of data being processed is easier said than done, and their legacy database was unable to deliver timely, meaningful insights without performance dips.

    In this case study, you’ll learn how PayPal was able to overcome the limitations of its legacy infrastructure with a cost-effective IT strategy and a NoSQL database system. Read on to discover how you can leverage a real-time data platform to fight fraud and protect your business.

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