Big Data - Past Present and future - an analyst's perspective
By: IBM View more from IBM >>
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Data governance 101: Creating a framework
By: Veritas
Type: eGuide
In order to become more data-driven, businesses need to think more strategically about governing the data they’re looking to be driven by.
As a result, implementing an effective data governance plan comes down to not only picking the right tools but coordinating multiple business units, getting them involved, and possibly rethinking your operating model.
In this expert e-guide, we explore how to create an enterprise data governance framework. Uncover some strategic best practices for big data governance so that you can boost data quality and prevent critical inconsistencies.
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Which SSD type deserves your data?
By: Micron Technology
Type: eGuide
Flash storage has built up quite the reputation for being fast. And when it comes to data analytics, SSDs don’t disappoint because solid-state technology can perform analytics on big data more efficiently. However, there’s a bit of a catch.
In this guide, storage expert – Phil Goodwin – discusses how flash storage technology is only advantageous in certain types of environments. Discover which kind of SSD deployment is best designed for your environment’s big data needs.
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3 steps to meet today's data challenges
By: SAS
Type: White Paper
Today’s data is complex, unstructured, and constantly moving at a rapid rate. It isn’t enough to know that data is big. In the new world of always-on data, you need to reimagine your relationship to data to improve the bottom line.
This resource lays out the 3 steps to transform your organization in order to meet today’s data challenges. Learn how to awaken your data, discover hidden value, and deploy your data-driven insights into processes or products.
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Spark Muscles Into Big Data Processing
By: TechTarget Data Management
Type: eBook
Armed with data processing, streaming and machine learning capabilities, the multitalented Apache Spark architecture is becoming a force in its own right.
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How Industrial DataOps is changing Industry 4.0
By: HighByte
Type: Blog
The change sweeping the manufacturing industry right now is so thorough that some are calling it “The 4th Industrial Revolution.” And with this change comes problems—namely the issue of unusable data. But with the right DataOps approach, you can start to make sense of these remarkably complex sets of data. Read on to learn more.
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How to build & scale operational data pipelines with OT systems
By: HighByte
Type: Analyst Report
Integrating and contextualizing operational data has proven to be difficult when it comes to technical execution. This brief by IDC provides insights on the challenges and opportunities facing the CIO as they strive to bridge operational technology (OT) and the line of business. Read on to learn how you can empower your IT and LoB.
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How you can combat data errors and other major challenges
By: InterSystems
Type: Research Content
A survey of 375 asset management firms shows data management challenges that organizations are struggling with, including:54% of firms are challenged by errors in data, largely due to the number of disparate data sources66% of respondents require 6 to 9 people to process data to meet the needs of business stakeholdersRead the full report here.
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Turn data into insights with AI and ML
By: Red Hat and Intel
Type: Infographic
The amount of data stored globally is expected to grow to 8.9 zettabytes by 2024. This infographic details how you can turn your data into a valuable business asset with artificial intelligence (AI) and analytics. See the full infographic here.
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4 practical use cases for integrating Industrial DataOps
By: HighByte
Type: Blog
Most manufacturing companies know how leveraging industrial data can improve production, but they remain challenged as to how to scale-up to the enterprise level. Read how these four use cases reveal the ways Industrial DataOps can integrate your role-based operational systems with your business IT systems as well as those of outside vendors.
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Best practices for enabling industrial DataOps
By: HighByte
Type: White Paper
Industrial DataOps is the dominant framework for mastering 4.0 data transformation projects, and it is key for leveraging solutions that can deliver data to users for a real-time view of the enterprise. Read on to learn about a solution that can help manage data in a common format that is ready to consume, contextualize, and scale for the customer.
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The Role of Data Management in a Modern Data Ecosystem (Replay)
By: Semarchy
Type: Webcast
Looking to explore the rise of Modern Data Ecosystems and new approaches to data management? Tune in to this webinar to keep up to date with today’s top data management challenges, with exclusive insights from leaders in the space.
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11 Insights to Help Quants Break Through Analytics Barriers
By: FD Technologies
Type: eBook
Whether you focus on trading analytics, quantitative modeling, risk management, or any other aspects of quantitative nance, finding insights faster has never been more critical. Read on to discover how you can leverage tools uniquely built for financial services to break down data and analytics barriers for your business.
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Changing priorities in ALM technology, data and analytics
By: SAS
Type: eBook
Discover in this e-book how financial service industry leaders are tackling an evolving business environment by integrating risk processes, strengthening scenario-based analytics, and modernising their ALM technology.
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Case study: How to reduce Amazon costs with Pepperdata
By: Pepperdata
Type: Case Study
In this case study, you'll find out how Autodesk reduced Amazon EMR costs by 50% and boosted performance with Pepperdata. Read on now to learn how this leading software company optimized its big data infrastructure and achieved significant savings.
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Discover strategies for managing data bias, privacy, and drift
By: OpenText
Type: eBook
Discover how to effectively manage data bias, privacy, and drift in the age of data sprawl. Learn five strategic best practices to ensure comprehensive data oversight, foster trust, and drive data-driven outcomes. Read the full e-book to learn more.