Jet Global

NOVEMBER 5, 2020

OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster. Option 3: Azure Data Lakes.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 87

Data Science Data Analytics Prescriptive Analytics Analytics 87

Timo Elliott

JANUARY 3, 2022

It’s stored in corporate data warehouses, data lakes, and a myriad of other locations – and while some of it is put to good use, it’s estimated that around 73% of this data remains unexplored. In this way, you can turn dark data into insights and help drive business improvements. Learn More.

IT 143

IT Unstructured Data Data Quality Machine Learning 143

Analytics Vidhya

MAY 29, 2023

The two pillars of data analytics include data mining and warehousing. They are essential for data collection, management, storage, and analysis. Providing insights into the trends, prediction, and appropriate strategy for the company and serving numerous other uses are distinct.

Data mining 294

Data mining Data Collection Strategy Data Analytics 294

CIO Business Intelligence

SEPTEMBER 14, 2023

They’re often responsible for building algorithms for accessing raw data, too, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

Cloudera

JANUARY 28, 2022

Then there are the more extensive discussions – scrutiny of the overarching, data strategy questions related to privacy, security, data governance /access and regulatory oversight. These are not straightforward decisions, especially when data breaches always hit the top of the news headlines.

Slice and Dice 109

Slice and Dice Cost-Benefit Risk Data Governance 109

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 98

Data Lake Sales Data Warehouse Snapshot 98

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

erwin

JUNE 26, 2020

If you’re serious about a data-driven strategy , you’re going to need a data catalog. Organizations need a data catalog because it enables them to create a seamless way for employees to access and consume data and business assets in an organized manner.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

Smart Data Collective

JUNE 7, 2019

Big Data is defined as a large volume of structured and unstructured data that a business comes across their day-to-day operations. However, the amount of data isn’t really a big deal. What’s important is the way organizations handle this data for the benefit of their businesses. Conclusion.

Big Data 81

Big Data Marketing Cost-Benefit Unstructured Data 81

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 109

Data Lake Analytics Dashboards Metrics 109

AWS Big Data

JANUARY 8, 2024

Stream ingestion – The stream ingestion layer is responsible for ingesting data into the stream storage layer. It provides the ability to collect data from tens of thousands of data sources and ingest in real time.

Analytics 109

Analytics IoT Data-driven Snapshot 109

CIO Business Intelligence

SEPTEMBER 21, 2023

Generative AI touches every aspect of the enterprise, and every aspect of society,” says Bret Greenstein, partner and leader of the gen AI go-to-market strategy at PricewaterhouseCoopers. Over the past 10 years, data has grown to be a company’s most valuable asset, the electricity that powers innovation and value creation.

Enterprise 130

Enterprise Consulting Modeling Cost-Benefit 130

Sisense

MAY 28, 2020

As enterprises demand data infrastructures that can meet this growth in real-time data — and ultimately assist with their product differentiation strategy — the pressure put on product teams is huge. Product teams are already having to manage the growing complexities that come with modern data environments.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

Cloudera

AUGUST 20, 2021

How CDP Enables and Accelerates Data Product Ecosystems. A multi-purpose platform focused on diverse value propositions for data products. Data Types and Sources: The multitude of data experiences enable efficient processing of different data types, such as structured and unstructured data collected from any potential source.

Strategy 94

Strategy Cost-Benefit Visualization Data Warehouse 94

Cloudera

NOVEMBER 25, 2020

Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL. Interview notes, patient information, and treatment history is a mixed set of semi-structured and unstructured data, often only accessed using proprietary, or less known, techniques and languages.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

AWS Big Data

MARCH 2, 2023

How Apache Iceberg addresses what customers want in modern data lakes More and more customers are building data lakes, with structured and unstructured data, to support many users, applications, and analytics tools. all_reviews ): data and metadata. tableProperty("format-version", "2").createOrReplace()

Data Lake 114

Data Lake Data Processing Metadata Snapshot 114

CIO Business Intelligence

NOVEMBER 25, 2022

Today, more than 90% of its applications run in the cloud, with most of its data is housed and analyzed in a homegrown enterprise data warehouse. Like many CIOs, Carhartt’s top digital leader is aware that data is the key to making advanced technologies work. Today, we backflush our data lake through our data warehouse.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

CIO Business Intelligence

MARCH 9, 2022

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. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. Meet the data lakehouse.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

CIO Business Intelligence

JUNE 29, 2022

The recent announcement of the Microsoft Intelligent Data Platform makes that more obvious, though analytics is only one part of that new brand. The recent announcement of the Microsoft Intelligent Data Platform makes that more obvious, though analytics is only one part of that new brand. Azure Data Factory. Microsoft.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

CIO Business Intelligence

AUGUST 18, 2022

The result is an emerging paradigm shift in how enterprises surface insights, one that sees them leaning on a new category of technology architected to help organizations maximize the value of their data. Enter the data lakehouse. You can intuitively query the data from the data lake.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

BizAcuity

MAY 10, 2022

Companies planning to scale their business in the next few years without a definite cloud strategy might want to reconsider. 14 years later, in 2020, the pandemic demands for remote work, and overnight revisions to business strategy. 2012: Amazon Redshift, the first of its kind cloud-based data warehouse service comes into existence.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

IBM Big Data Hub

MAY 9, 2023

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics. What is watsonx.data?

Data Warehouse 82

Data Warehouse Cost-Benefit Recreation/Entertainment Unstructured Data 82

BizAcuity

APRIL 14, 2022

Netflix uses big data to make decisions on new productions, casting and marketing and generate millions in revenue through successful and strategic bets. Data Management. Before building a big data ecosystem, the goals of the organization and the data strategy should be very clear. Unstructured Data Management.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

CIO Business Intelligence

MAY 24, 2022

Australian research and advisory firm Adapt identifies an organisation’s ability to execute a data-driven strategy as one of 12 core competencies , identified from 30,000 conversations spanning three years with leading IT and businesses. This is the first post in a series of three on data-driven organisations.

Data-driven 98

Data-driven Data Lake Data Warehouse Cost-Benefit 98

FineReport

JUNE 24, 2021

Business intelligence solutions are a whole combination of technology and strategy, used to handle the existing data of the enterprises effectively. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

Smart Data Collective

SEPTEMBER 26, 2021

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. Working with massive structured and unstructured data sets can turn out to be complicated. Preserve information: Keep your raw data raw.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

Sisense

MAY 28, 2019

For the leaders that acquire or merge with other emerging leaders , this type of convergence is a strategy to accelerate growth, expand capabilities, and deliver on product roadmaps years ahead of schedule. Two orthogonal approaches to data analytics have developed in this decade of BI: 1. The truth always rises to the surface.

Data Analytics 89

Data Analytics Data Lake Analytics Unstructured Data 89

FineReport

DECEMBER 27, 2021

Enterprise BI typically functions by combining enterprise data warehouse and enterprise license to a BI platform or toolset that business users in various roles can use. Usually, enterprise BI incorporates relatively rigid, well-structured data models on data warehouses or data marts. Enterprise BI tools.

Enterprise 59

Enterprise Dashboards Business Intelligence Visualization 59

Sisense

JUNE 30, 2020

Prescriptive analytics takes things a stage further: In addition to helping organizations understand causes, it helps them learn from what’s happened and shape tactics and strategies that can improve their current performance and their profitability. A simple example would be the analysis of marketing campaigns.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Production Monitoring Only.

Testing 307

Testing Machine Learning Consulting Data Quality 307

Sisense

JULY 22, 2020

The growing amount and increasingly varied sources of data that every organization generates make digital transformation a daunting prospect. At Sisense, we’re dedicated to making this complex task simple, putting power in the hands of the builders of business data and strategy, and providing insights for everyone.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

datapine

FEBRUARY 22, 2022

1) What Is A Business Intelligence Strategy? 2) BI Strategy Benefits. 4) How To Create A Business Intelligence Strategy. Over the past 5 years, big data and BI became more than just data science buzzwords. Your Chance: Want to build a successful BI strategy today? What Is A Business Intelligence Strategy?

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Sisense

MAY 11, 2021

In this article, we’ll dig into what data modeling is, provide some best practices for setting up your data model, and walk through a handy way of thinking about data modeling that you can use when building your own. Building the right data model is an important part of your data strategy. Discover why.

Modeling 84

Modeling Big Data IoT Data Warehouse 84