ComputerWeekly.com Research Library

Powered by Bitpipe.com

All Research Sponsored By:Dremio

  • Top 5 Data Science Industry Predictions for 2020

    The new decade promises to be a big one for new technology developments; what, exactly, does 2020 hold for the data science industry? Watch this webinar to learn 5 predictions for data science in 2020, including changes to the IoT, big data architecture, cloud data lakes and warehouses, and more.

  • Unlocking Data Science on the Data Lake using Dremio, NLTK and Spacy

    A quality data pipeline, one that is able to access all of your information in disparate sources, can give your data scientists a holistic view of the data instantly—giving them more time to analyze it. Read this resource to see how Dremio can empower your business to build your own pipeline to streamline data access from a variety of sources.

  • BI On Big Data: What Are Your Options?

    The advent of big data changed data analytics, but not necessarily for the better. Right now, companies often struggle to turn the massive amounts of data that they’ve collected into useful, unified data sets. Download this ebook by Dremio to examine some of the challenges and trends in the data management world right now.

  • Dremio Architecture Guide

    Having quality data architecture can allow your organization to stop managing your data and start using it, but achieving this is often easier said than done. Read this Dremio architecture guide to learn how their data lake engine can help you easily navigate and use your data lake.

  • Self-Service Analytics

    For today’s organizations, the complexity of data, the speed with which it changes, and the massive amounts of it make modern data analysis an extremely complex, IT-dependent task. Read this white paper by CITO Research, sponsored by Dremio, and see how you can free up your IT staff while empowering your employees.

  • Dremio Security Architecture Guide

    Because data sets and analytics systems are valuable targets for cybercriminals, it is important that your data access and analysis systems provide a variety of security options so that you can protect your organization’s data from potential threats. Read the attached guide to see some security choices that the data lake engine Dremio offers.

  • Vectorized Query Processing Using Apache Arrow

    Apache Arrow is popular for many reasons: it can interact with a variety of languages, is an open source project, and facilities speed within your database. It is a versatile tool that can be used to maximize hardware functionality and utilize vectorized query processing.Watch this webinar to learn more about vectorized query processing.

  • Dremio Architecture Guide

    Most organizations deposit their raw data in data lakes, where it can be stored easily. But it can require a complex series of programs, tasks, and pipelines to leverage this data into analytics insights.Read this guide to learn how Dremio can use your data lake and allow your business to derive analytics insights directly from your data.

  • Analyzing Multiple Stream Data Sources using Dremio and Python

    Data processing is a complex series of tasks – data of different kinds and formats need to be aggregated into a single database that easily accessible to users across your organization. Read this tutorial to learn how Dremio can unify data from disparate sources into a single dataset, ready to be utilized by an analytics or data science program.

  • Using Data-driven Permissions to Secure Your Data Lake

    When managing a data lake, it is important to make sure that this data is secured for a variety of reasons.How does your business implement data lake security features? Additionally, how customizable are these security tools?Read this white paper and learn how you can create your own data lake permissions with Dremio.

  • Running SQL Based Workloads In The Cloud

    Having a data lake engine that’s flexible enough to handle a variety of workloads in an setting is important to a business like yours. Watch this webinar to learn about some of the specific applications of Dremio and learn how it can handle various SQL-workloads in the cloud.

  • Using a Data Lake Engine to Create a Scalable Data Pipeline

    Your organization should have a data pipeline that can access all of your data stored across one or more disparate sources. But how do you know if your pipeline is efficient and cost-effective? Watch this webcast to learn how you can create your own, scalable data pipeline using the data lake engine Dremio.

  • Data Reflections

    Watch this webinar to learn how Dremio is compatible with various Apache products, as well as how to use it to create data reflections and reduce distance to data to accelerate query search speeds while reducing resource requirements and latency.

  • Querying Hive 3 Transactional Tables with Dremio

    Making effective use of your Hadoop data warehouses is an essential feature of any data integration or data management tool. Read this guide and find out how the data lake engine Dremio can help you maximize what you are able to get out of Hive 3 and its advanced transactions.

  • Interactive Data Science and BI on the Hadoop Data Lake

    Simplifying your data pipeline and reducing your reliance on complicated IT processes is critical—not only make it easier to access your information, but also to help manage future changes to your data architecture, like moving to the cloud.Watch this webcast to learn how Dremio can interact with a variety of data repositories.

  • Enabling Self-Service Interactive Analytics on All of Your Data

    A self-service analytics tool is essential for any company handling big data, but finding one that exists on top of your existing data architecture is a challenge. Watch this webinar to see how Dremio can function not just as a data lake engine, but also as an analytics tool that easily fits into your existing infrastructure, regardless of size.

  • Creating a Cloud Data Lake for Any Company

    A quality data lake engine will allow your business to democratize data access, easily querying and accessing your information without requiring a specific storage system or search format. Data democratization can help you cut costs and increase productivity. Access this webcast to learn how Dremio can help create a useful cloud data lake for you.

  • Dremio Deployments Guide

    Scalability, query speed and quality, and cross-database search abilities are all essential features of any data integration software. Efficient data management allows your business to use your existing data storage in a more effective way.Read more about how Dremio’s data lake engine allows your business to start optimizing your data lake usage.

  • Fundamental Considerations of Moving to the Cloud Data Lake

    Moving data to the cloud could result in downtime and other issues. However, moving to the cloud offers several advantages including scalable storage, centralizing data, and more.Read this article to learn the essential considerations you must make when deciding if you should switch your business to the cloud, and the ways in which Dremio can help.

  • One of the potential uses for Dremio

    Most modern databases aren’t made up of one single source. Instead, many organizations find themselves storing data across disparate sources. This structure can make it difficult to integrate your data without losing quality and efficiency. Open this guide to read about how Dremio allows you easily work with two sources at once.

  • Simplifying Data Pipeline

    When it comes to your data pipeline, you want to optimize your data queries and let your analysts to focus on what they do best—analyze data, not retrieve it. Watch this webcast in which Dremio explains their Data Lake Engine and how it can organize your data, customize its curation, and track its linage while removing barriers to query speed.

  • Conquering Slow Dirty And Distributed Data With Apache Arrow And Dremio

    Long gone are the days when you could point an analytics tool at one particular database or file and satisfy all data your needs. High variety and volume keeps us on our toes - and demands for data are growing rapidly. Watch this webinar for a discussion on conquering slow, dirty and distributed data with Apache Arrow and Dremio.

  • Making BI Work With a Data Lake

    In this webcast, listen as Kelly Stirman, the VP of Strategy at Dremio, talks about the idea of making BI work on a data lake. Also, explore some of the concepts and patterns that many companies see as they embark on their journey to make data lake a key part of their analytic strategy.

Bitpipe Definitions: A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Other

ComputerWeekly.com Research Library Copyright © 1998-2020 Bitpipe, Inc. All Rights Reserved.

Designated trademarks and brands are the property of their respective owners.

Use of this web site constitutes acceptance of the Bitpipe Terms and Conditions and Privacy Policy.