Data Science 101

JUNE 10, 2019

Getting your first data science job might be challenging, but it’s possible to achieve this goal with the right resources. Before jumping into a data science career , there are a few questions you should be able to answer: How do you break into the profession? What skills do you need to become a data scientist?

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Analytics Vidhya

OCTOBER 10, 2022

This article was published as a part of the Data Science Blogathon. Introduction Most of you would know the different approaches for building a data and analytics platform. You would have already worked on systems that used traditional warehouses or Hadoop-based data lakes. Selecting one among […].

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CIO Business Intelligence

MARCH 25, 2025

Data debt that undermines decision-making In Digital Trailblazer , I share a story of a private company that reported a profitable year to the board, only to return after the holiday to find that data quality issues and calculation mistakes turned it into an unprofitable one.

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TDAN

NOVEMBER 17, 2020

Top-quality data currently represents one of the most important resources for any company. Startups that lack familiarity with important tendencies and trends in their industry need to have this crucial data […].

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Data Science Marketing Data Architecture Data Strategy 145

AWS Big Data

JANUARY 15, 2025

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Two use cases illustrate how this can be applied for business intelligence (BI) and data science applications, using AWS services such as Amazon Redshift and Amazon SageMaker.

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Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Towards Data Science ). Solutions that support MDAs are purpose-built for data collection, processing, and sharing.

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KDnuggets

FEBRUARY 10, 2022

Going forward, data professionals have found a new way to address the scalability of sources through data mesh.

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DataKitchen

DECEMBER 30, 2020

DataKitchen provides an end-to-end DataOps platform that automates and coordinates people, tools, and environments in the entire data analytics organization—from orchestration, testing, and monitoring to development and deployment. CRN’s The 10 Hottest Data Science & Machine Learning Startups of 2020 (So Far).

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Testing Big Data Statistics Manufacturing 241

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

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IBM Big Data Hub

JANUARY 5, 2023

But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality. What does a modern data architecture do for your business? Reduce data duplication and fragmentation.

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Data Virtualization

OCTOBER 3, 2024

Reading Time: 3 minutes As organizations continue to pursue increasingly time-sensitive use-cases including customer 360° views, supply-chain logistics, and healthcare monitoring, they need their supporting data infrastructures to be increasingly flexible, adaptable, and scalable.

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Data Virtualization

OCTOBER 5, 2022

Reading Time: 3 minutes At the heart of every organization lies a data architecture, determining how data is accessed, organized, and used. For this reason, organizations must periodically revisit their data architectures, to ensure that they are aligned with current business goals.

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DataKitchen

MAY 10, 2021

Your IDB practices won’t succeed unless your leaders commit to attracting and retaining data and analytics talent, developing data science and other data and analytical skills, establishing centers of excellence (COEs), and improving the overall data literacy of all employees.”

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CIO Business Intelligence

AUGUST 9, 2022

These generalists are often responsible for every step of the data process, from managing data to analyzing it. Dataquest says this is a good role for anyone looking to transition from data science to data engineering, as smaller businesses often don’t need to engineer for scale. Data engineer vs. data architect.

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Analytics Data Science Statistics Unstructured Data 131

CIO Business Intelligence

SEPTEMBER 14, 2023

These generalists are often responsible for every step of the data process, from managing data to analyzing it. Dataquest says this is a good role for anyone looking to transition from data science to data engineering, as smaller businesses often don’t need to engineer for scale.

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AWS Big Data

DECEMBER 4, 2024

With this launch, you can query data regardless of where it is stored with support for a wide range of use cases, including analytics, ad-hoc querying, data science, machine learning, and generative AI.

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DataKitchen

JUNE 12, 2023

We had been talking about “Agile Analytic Operations,” “DevOps for Data Teams,” and “Lean Manufacturing For Data,” but the concept was hard to get across and communicate. I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science.

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CIO Business Intelligence

NOVEMBER 28, 2023

Data, of course, has been all the rage the past decade, having been declared the “new oil” of the digital economy. And yes, data has enormous potential to create value for your business, making its accrual and the analysis of it, aka data science, very exciting.

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CIO Business Intelligence

NOVEMBER 25, 2022

As part of that transformation, Agusti has plans to integrate a data lake into the company’s data architecture and expects two AI proofs of concept (POCs) to be ready to move into production within the quarter. Like many CIOs, Carhartt’s top digital leader is aware that data is the key to making advanced technologies work.

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CIO Business Intelligence

MARCH 18, 2024

Meanwhile, SAP is leveraging NVIDIA’s accelerated computing platforms and NVIDIA AI Enterprise data science software, including Nvidia Rapids, Rapids cuDF, and cuML, to make it easier for data scientists to access data and enhance ML workload performance in Datasphere.

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Cloudera

JUNE 7, 2022

Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform. We deliver cloud-native data analytics across the full data lifecycle – data distribution, data engineering, data warehousing, transactional data, streaming data, data science, and machine learning – that’s portable across infrastructures.

IT 112

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Data Virtualization

SEPTEMBER 21, 2023

Reading Time: 2 minutes In the ever-evolving landscape of data management, one concept has been garnering the attention of companies and challenging traditional centralized data architectures. This concept is known as “data mesh,” and it has the potential to revolutionize the way organizations handle.

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AWS Big Data

NOVEMBER 7, 2024

She has helped many customers build large-scale data warehouse solutions in the cloud and on premises. She is passionate about data analytics and data science. Milind Oke is a Data Warehouse Specialist Solutions Architect based out of New York.

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Cloudera

SEPTEMBER 24, 2021

As data volumes soared – particularly with the rise of smartphones – appliance based models became eye-wateringly expensive and inflexible. They were using R and Python, with NoSQL and other open source ad hoc data stores, running on small dedicated servers and occasionally for small jobs in the public cloud.

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Dataiku

JULY 13, 2022

Every business function struggles with scale, including AI and data science. Architects have addressed technical scale to increase productivity — blazing fast connections, big data architectures, faster chips, distributed computing, massively parallel processing, and all sorts of optimized hardware stacks for AI.

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CIO Business Intelligence

MARCH 9, 2022

However, it also supports the quality, performance, security, and governance strengths of a data warehouse. As such, the lakehouse is emerging as the only data architecture that supports business intelligence (BI), SQL analytics, real-time data applications, data science, AI, and machine learning (ML) all in a single converged platform.

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Cloudera

NOVEMBER 7, 2023

Are you struggling to manage the ever-increasing volume and variety of data in today’s constantly evolving landscape of modern data architectures? If you are interested in learning more about how to use Apache Ozone to power data science, this is a great article.

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Cloudera

OCTOBER 11, 2022

This leads to the obvious question – how do you do data at scale ? Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. And that data is likely in clouds, in data centers and at the edge.

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CIO Business Intelligence

JUNE 23, 2022

Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform. We deliver cloud-native data analytics across the full data lifecycle – data distribution, data engineering, data warehousing, transactional data, streaming data, data science, and machine learning – that’s portable across infrastructures.

IT 97

IT Data Architecture Unstructured Data Big Data 97

CDW Research Hub

JULY 18, 2022

Snowflake enables a wide variety of workloads and applications on any cloud, including data warehouses, data lakes, data pipelines and data sharing, as well as business intelligence, data science and data analytics applications. Overall data architecture and strategy.

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CIO Business Intelligence

APRIL 25, 2022

“You can think that the general-purpose version of the Databricks Lakehouse as giving the organization 80% of what it needs to get to the productive use of its data to drive business insights and data science specific to the business.

Recreation/Entertainment 119

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Cloudera

NOVEMBER 18, 2020

The technological linchpin of its digital transformation has been its Enterprise Data Architecture & Governance platform. It hosts over 150 big data analytics sandboxes across the region with over 200 users utilizing the sandbox for data discovery.

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AWS Big Data

NOVEMBER 13, 2023

The downstream consumers consist of business intelligence (BI) tools, with multiple data science and data analytics teams having their own WLM queues with appropriate priority values. Consequently, there was a fivefold rise in data integrations and a fivefold increase in ad hoc queries submitted to the Redshift cluster.

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DataKitchen

JANUARY 3, 2022

For example, teams working under the VP/Directors of Data Analytics may be tasked with accessing data, building databases, integrating data, and producing reports. Data scientists derive insights from data while business analysts work closely with and tend to the data needs of business units.

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CIO Business Intelligence

MAY 2, 2022

Ken Finnerty, vice president of information technology at overall winner UPS , will discuss how the shipping giant thinks about innovation and tools like artificial intelligence and data architecture with Chandana Gopal, IDC’s research director for Future of Intelligence. The event is free to attend for qualified attendees.

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Advertising Data Governance Insurance Data-driven 98

Cloudera

SEPTEMBER 28, 2020

The data lifecycle model ingests data using Kafka, enriches that data with Spark-based batch process, performs deep data analytics using Hive and Impala, and finally uses that data for data science using Cloudera Data Science Workbench to get deep insights.

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