Five Things to Consider When Choosing a Data Catalog

February 20, 2019

The self-service data analytic journey often begins with choosing a data catalog. Before businesses can make the most of their corporate data, analysts need the ability to find and use trusted data, share insights about that data, crowdsource quality attributes and have recommendations presented that relate to data sources that have been discovered.Organizations face growing challenges. The volume of data is exploding and coming from various sources structured, unstructured data, IoT, the cloud, etc. thus, driving the growth of the business analytics market. But not all data catalog solutions are the same. The four distinct data catalog types include:Data Lake Catalog works well if all your data is in a single data lake.Data Warehouse Catalog is more ideal for legacy data warehouses and data management.Cloud Catalog for vendors who offer cloud compute and storage, predisposes you have all your data in their cloud.Enterprise Data Catalog does not discriminate where your data is, what structure it is in or any other restriction, but establishes a virtual data layer to bring all your catalog data into one centralized place.

Spotlight

ClearStory Data

ClearStory Data is bringing Data Intelligence to everyone to accelerate the way business leaders get answers from more data, on a faster cycle, across any number of disparate data sources. ClearStory Data’s solution simplifies data access to internal and external sources, automates data harmonization via Intelligent Data Harmonization™ across disparate data, enables fast, collaborative exploration, and reduces business wait times for insights via Interactive, Collaborative StoryBoards™. ClearStory Data lets business users be more self-reliant on reaching richer, faster insights. Its end-to-end solution includes an integrated Spark-based data processing platform and an incredibly simple user application model for business consumption of insights. The company is headquartered in Menlo Park, CA and backed by Andreessen Horowitz, DAG Ventures, Google Ventures, Khosla Ventures and Kleiner Perkins Caufield & Byers (KPCB).

OTHER WHITEPAPERS
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THE COMPUTEINFRASTRUCTURE NEEDED FOR PREDICTIVE ANALYTICS

whitePaper | November 26, 2019

Modernized organizations are leveraging the transformative benefits of predictive analytics to propel their business forward. Predictive analytics arm you with knowledge and insights that can make the difference between profits and losses. They use modeling, machine learning, and artificial intelligence to analyze current data and make predictions about the future. Every industry can benefit from predictive analytics. Those who ignore the potential here are squandering a huge opportunity to grow or create better experiences. The recent dramatic progress in AI-based predictive analytics and machine learning provides organizations with the power to unlock tremendous value from previously hard to decipher data. Through the power of AI-enabled infrastructure, you can harness the predictive analytics/machine learning wave and gain business advantages that will not only keep you in the game, but at the leading edge. Automated server capabilities and the right server for the job will get you where you need to go. This eBook focuses in on how server automation, along with the right servers for the workload, empowers companies to make great strides in the world of machine learning and predictive analytics.

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How to Analyze and Maximize Customer Retention: Asset

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Understanding all the factors that impact customer health and retention requires a comprehensive view of complex data.

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On Artificial Intelligence A European approach to excellence and trust

whitePaper | February 19, 2020

Artificial Intelligence is developing fast. It will change our lives by improving healthcare (e.g. making diagnosis more precise, enabling better prevention of diseases), increasing the efficiency of farming, contributing to climate change mitigation and adaptation, improving the efficiency of production systems through predictive maintenance, increasing the security of Europeans, and in many other ways that we can only begin to imagine. At the same time, Artificial Intelligence (AI) entails a number of potential risks, such as opaque decision-making, gender-based or other kinds of discrimination, intrusion in our private lives or being used for criminal purposes.

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With over 2,800 campaigns each year delivered through a team of 300+ digital, data, and technology specialists, Deck 7 is a first resource for B2B demand generation services for marketers worldwide. Clients leverage Deck 7’s multichannel content marketing services and Media 7’s network of 30+ online publications for content syndication to engage over 95 million buyers across 16 industries and 120+ countries.

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Enterprise Data Orchestration

whitePaper | June 3, 2021

Data growth continues at an exponential rate even as cloud architectures make data management more complex and advanced applications necessitate more data movement. So what can be done to enable clean data capture and movement across an enterprise? Read this white paper to learn the requirements for data orchestration at scale and discover how you can build a holistic data architecture that enables successful DataOps.

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Evolving Role of Data Scientist in the Age of Personalization

whitePaper | March 12, 2020

This point of view is an exploration of the possibilities engendered by rethinking the role of data scientists in the wake of industrial revolution. It might be claimed that current trends in industrial revolution reflect a paradigm shift towards data centric processing with data science playing an increasingly critical role. This point of view also explicitly highlights the potential role of Data scientists as an emerging phenomenon, and then to show some of the benefits that this role can bring as we move towards industrial disruption

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Spotlight

ClearStory Data

ClearStory Data is bringing Data Intelligence to everyone to accelerate the way business leaders get answers from more data, on a faster cycle, across any number of disparate data sources. ClearStory Data’s solution simplifies data access to internal and external sources, automates data harmonization via Intelligent Data Harmonization™ across disparate data, enables fast, collaborative exploration, and reduces business wait times for insights via Interactive, Collaborative StoryBoards™. ClearStory Data lets business users be more self-reliant on reaching richer, faster insights. Its end-to-end solution includes an integrated Spark-based data processing platform and an incredibly simple user application model for business consumption of insights. The company is headquartered in Menlo Park, CA and backed by Andreessen Horowitz, DAG Ventures, Google Ventures, Khosla Ventures and Kleiner Perkins Caufield & Byers (KPCB).

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