CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

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Data Lake Unstructured Data Data Warehouse Big Data 119

Sisense

MAY 28, 2019

2019 can best be described as an era of modern cloud data analytics. Convergence in an industry like data analytics can take many forms. We have seen industry rollups in which firms create a collection of analytical tools under one brand. The allure of operationalizing BI in-data is its perceived simplicity.

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Data Analytics Data Lake Analytics Unstructured Data 89

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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Data Lake Analytics Snapshot Data Quality 93

CIO Business Intelligence

NOVEMBER 25, 2022

Carhartt’s signature workwear is near ubiquitous, and its continuing presence on factory floors and at skate parks alike is fueled in part thanks to an ongoing digital transformation that is advancing the 133-year-old Midwest company’s operations to make the most of advanced digital technologies, including the cloud, data analytics, and AI.

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Data Lake Data Warehouse Unstructured Data Data Architecture 128

AWS Big Data

FEBRUARY 26, 2025

Analytics remained one of the key focus areas this year, with significant updates and innovations aimed at helping businesses harness their data more efficiently and accelerate insights. This zero-ETL integration reduces the complexity and operational burden of data replication to let you focus on deriving insights from your data.

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Analytics Data Lake Metadata Data Warehouse 59

Sisense

APRIL 26, 2020

Different types of information are more suited to being stored in a structured or unstructured format. Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Unstructured data.

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Unstructured Data Data Warehouse Structured Data Data mining 52

AWS Big Data

AUGUST 3, 2023

With the rapid growth of technology, more and more data volume is coming in many different formats—structured, semi-structured, and unstructured. Data analytics on operational data at near-real time is becoming a common need. Then we can query the data with Amazon Athena visualize it in Amazon QuickSight.

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Data Lake Visualization Dashboards Insurance 87

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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AWS Big Data

FEBRUARY 29, 2024

Data governance is a critical building block across all these approaches, and we see two emerging areas of focus. First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses.

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Data Governance Unstructured Data Metadata Data Lake 109

CIO Business Intelligence

JUNE 29, 2022

And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done. For many enterprises, Microsoft Azure has become a central hub for analytics. Azure Data Explorer. Azure Data Lake Analytics.

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Data Lake Analytics Data Warehouse Machine Learning 116

Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new.

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Data Analytics Analytics Unstructured Data Data mining 69

AWS Big Data

JUNE 26, 2024

New feature: Custom AWS service blueprints Previously, Amazon DataZone provided default blueprints that created AWS resources required for data lake, data warehouse, and machine learning use cases. You can build projects and subscribe to both unstructured and structured data assets within the Amazon DataZone portal.

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Data Lake Data Warehouse Unstructured Data Data Governance 102

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

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Data Lake Dashboards Cost-Benefit Data Warehouse 52

Cloudera

NOVEMBER 17, 2022

The Solution: CDP Private Cloud brings a next-generation hybrid architecture with cloud-native benefits to HBL’s data platform. HBL started their data journey in 2019 when data lake initiative was started to consolidate complex data sources and enable the bank to use single version of truth for decision making.

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Management Data Lake Consulting Unstructured Data 85

BizAcuity

APRIL 14, 2022

Its effective data analytics that allows personalization in marketing & sales, identifying new opportunities, making important decisions and being sustainable for the long term. Competitive Advantages to using Big Data Analytics. The majority of the data a business has stored is generally unstructured.

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Big Data Data Analytics Management Unstructured Data 52

AWS Big Data

MAY 28, 2024

Large language models (LLMs) such as Anthropic Claude and Amazon Titan have the potential to drive automation across various business processes by processing both structured and unstructured data. Redshift Serverless is a fully functional data warehouse holding data tables maintained in real time.

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Unstructured Data Data Warehouse Structured Data Testing 102

AWS Big Data

MARCH 25, 2024

This data store provides your organization with the holistic customer records view that is needed for operational efficiency of RAG-based generative AI applications. For building such a data store, an unstructured data store would be best. This is typically unstructured data and is updated in a non-incremental fashion.

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Data Lake Unstructured Data Management Snapshot 104

AWS Big Data

MARCH 2, 2023

Many organizations are building data lakes to store and analyze large volumes of structured, semi-structured, and unstructured data. In addition, many teams are moving towards a data mesh architecture, which requires them to expose their data sets as easily consumable data products.

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Data Lake Testing Interactive Unstructured Data 83

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? Why is data analytics important for travel organizations?

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Data Analytics Analytics Data-driven Big Data 52

IBM Big Data Hub

MAY 19, 2023

In addition, to address the data loss issue, PT Aegis suggested replication and backups to IBM Cloud Object Storage , a highly scalable and secure cloud storage service that provides a flexible and cost-effective way to store and manage large amounts of unstructured data.

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Unstructured Data Data Processing Manufacturing Data Lake 74

Jet Global

OCTOBER 30, 2020

Introducing Data Lakes. Microsoft’s next option is called Azure Data Lake Services (ADLS), and it seems to be the company’s favored long-term solution to its D365 F&SCM reporting challenge. Data lake” is a generic term that refers to a fairly new development in the world of big data analytics.

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Data Lake Unstructured Data Reporting Finance 52

Andrew White

DECEMBER 9, 2019

Analytical quality and analytics. Downstream in the analytics pipeline. Scope could be: Data (i.e. Information (processed data). Analytic (the analytics itself). Records (files, or what you might all unstructured data). Images (i.e. Events or transactions. Anything else you can think of.

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Analytics Data Lake Data Governance Data Warehouse 66

Alation

AUGUST 4, 2022

Many CIOs argue the rise of big data pushed people to use data more proactively for business decision-making. Big data got“ more leaders and people in the organization to use data, analytics, and machine learning in their decision making,” says former CIO Isaac Sacolick. Big data can grow too big fast.

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Big Data Digital Transformation Data Lake Data-driven 95

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

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Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

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Analytics IoT Data-driven Snapshot 123

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

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Data Architecture Data Lake Machine Learning Data Governance 59

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. Big data analytics case study: SkullCandy.

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Alation

FEBRUARY 13, 2020

At some level, every enterprise is struggling to connect data to decision-making. In The Forrester Wave: Machine Learning Data Catalogs, 36% to 38% of global data and analytics decision makers reported that their structured, semi-structured, and unstructured data each totaled 1,000 TB or more in 2017, up from only 10% to 14% in 2016.

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ROI Cost-Benefit Unstructured Data Data Lake 52

BizAcuity

MAY 10, 2022

Google launches BigQuery, its own data warehousing tool and Microsoft introduces Azure SQL Data Warehouse and Azure Data Lake Store. Businesses find the need to manage unstructured data efficiently as a major business problem. Data lakes or data lake houses alone cannot solve the efficiency problem.

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Data-driven IoT Unstructured Data Data Lake 52

Cloudera

NOVEMBER 15, 2024

However, there is a fundamental challenge standing in the way of being successful: data. Unstructured data not ready for analysis: Even when defenders finally collect log data, it’s rarely in a format that’s ready for analysis.

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Analytics Metadata Snapshot Data-driven 59

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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Data Architecture Data Quality Strategy Data Lake 52

AWS Big Data

FEBRUARY 21, 2023

It is a data modeling methodology designed for large-scale data warehouse platforms. What is a data vault? The data vault approach is a method and architectural framework for providing a business with data analytics services to support business intelligence, data warehousing, analytics, and data science needs.

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Data Warehouse Data Lake Cost-Benefit Metadata 70

Cloudera

AUGUST 21, 2020

Perhaps one of the most significant contributions in data technology advancement has been the advent of “Big Data” platforms. Historically these highly specialized platforms were deployed on-prem in private data centers to ensure greater control , security, and compliance. Streaming data analytics. .

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Cost-Benefit Big Data ROI Risk 76

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. She also wants to predict future sales of both shoes and jewelry.

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Metadata Data Quality Data-driven Data Governance 52

CIO Business Intelligence

MAY 24, 2022

Organisations have to contend with legacy data and increasing volumes of data spread across multiple silos. To meet these demands many IT teams find themselves being systems integrators, having to find ways to access and manipulate large volumes of data for multiple business functions and use cases. Oil and Gas.

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Data-driven Data Lake Data Warehouse Machine Learning 98

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

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Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

OCTOBER 1, 2024

Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive data transformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases.

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Dashboards Data Lake Reporting Cost-Benefit 52