Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Cloudera

NOVEMBER 25, 2020

How could Matthew serve all this data, together , in an easily consumable way, without losing focus on his core business: finding a cure for cancer. The Vision of a Discovery Data Warehouse. A Discovery Data Warehouse is cloud-agnostic. Access to valuable data should not be hindered by the technology.

Data Warehouse 58

Data Warehouse Unstructured Data Analytics Visualization 58

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 122

Data Architecture Data Warehouse Statistics Visualization 122

IBM Big Data Hub

APRIL 25, 2023

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.

Optimization 56

Optimization Strategy Data Warehouse Cost-Benefit 56

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 97

Data Governance Unstructured Data Metadata Data Lake 97

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 139

Data Lake Data Warehouse Unstructured Data Business Intelligence 139

Jen Stirrup

MARCH 29, 2023

What does a sound, intelligent data foundation give you? It can give business-oriented data strategy for business leaders to help drive better business decisions and ROI. It can also increase productivity by enabling the business to find the data they need when the business teams need it. Why is this interesting?

Metadata 121

Metadata Data Warehouse Data Integration Business Intelligence 121

Smart Data Collective

JULY 9, 2023

ETL is a three-step process that involves extracting data from various sources, transforming it into a consistent format, and loading it into a target database or data warehouse. Extract The extraction phase involves retrieving data from diverse sources such as databases, spreadsheets, APIs, or other systems.

Data Quality 85

Data Quality Data Warehouse Data-driven Reporting 85

IBM Big Data Hub

OCTOBER 4, 2023

Artificial intelligence (AI) is now at the forefront of how enterprises work with data to help reinvent operations, improve customer experiences, and maintain a competitive advantage. It’s no longer a nice-to-have, but an integral part of a successful data strategy.

Data Lake 79

Data Lake Metadata Cost-Benefit Data Warehouse 79

AWS Big Data

MARCH 18, 2024

With these new attributes, you are able to build a segmentation model to identify distinct groups of customers that you can target with personalized messaging. This data is available to subscribe to on AWS Data Exchange—and with data sharing, you don’t need to pay to store a copy of it in your account in order to query it.

Data Warehouse 83

Data Warehouse Visualization Snapshot Data-driven 83

Timo Elliott

JANUARY 6, 2022

Data is delivered in context, enabling you to make better business decisions faster. Data sense-making. Storing data isn’t enough. Data analysis and exploration. To sharpen your data strategy skills, download this outcome-driven data strategy masterclass.

IT 133

IT Metadata Data-driven Data Governance 133

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 78

Data Science Data Analytics Prescriptive Analytics Analytics 78

AWS Big Data

NOVEMBER 14, 2023

However, in many organizations, data is typically spread across a number of different systems such as software as a service (SaaS) applications, operational databases, and data warehouses. Such data silos make it difficult to get unified views of the data in an organization and act in real time to derive the most value.

IoT 55

IoT Data-driven Data Lake Data Strategy 55

AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. One important aspect to a successful data strategy for any organization is data governance.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

CIO Business Intelligence

MAY 16, 2022

From the factory floor to online commerce sites and containers shuttling goods across the global supply chain, the proliferation of data collected at the edge is creating opportunities for real-time insights that elevate decision-making. The concept of the edge is not new, but its role in driving data-first business is just now emerging.

IoT 75

IoT Data Warehouse Internet of Things Machine Learning 75

AWS Big Data

FEBRUARY 27, 2024

The following are the key components of the Bluestone Data Platform: Data mesh architecture – Bluestone adopted a data mesh architecture, a paradigm that distributes data ownership across different business units. This enables data-driven decision-making across the organization.

Data-driven 97

Data-driven Data Lake Data Quality Data Governance 97

BizAcuity

APRIL 1, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. Data governance and security measures are critical components of data strategy. Data is susceptible to breach due to a number of reasons.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

CDW Research Hub

APRIL 20, 2020

Many organizations move from a traditional data warehouse to a hybrid or cloud-based data warehouse to help alleviate their struggles with rapidly expanding data, new users and use cases, and a growing number of diverse tools and applications. Connecting ThoughtSpot and Snowflake is a simple 3-step process.

Data Warehouse 52

Data Warehouse Consulting Data-driven Structured Data 52

CIO Business Intelligence

FEBRUARY 16, 2023

Hence the drive to provide ML as a service to the Data & Tech team’s internal customers. All they would have to do is just build their model and run with it,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. The offensive side?

Unstructured Data 98

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 98

BizAcuity

JANUARY 31, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. Data governance and security measures are critical components of data strategy. Data is susceptible to breach due to a number of reasons.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

CIO Business Intelligence

APRIL 12, 2023

Most current data architectures were designed for batch processing with analytics and machine learning models running on data warehouses and data lakes. What level of alerting, observability, and profiling can be counted on to ensure trust in the data by the business? It isn’t easy.

Machine Learning 126

Machine Learning Cost-Benefit Data-driven Strategy 126

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 113

Slice and Dice Cost-Benefit Risk Data Governance 113

TDAN

APRIL 19, 2022

Introduction We are living in the age of a data revolution, and more corporations are realizing that to lead—or in some cases, to survive—they need to harness their data wealth effectively.

Data Warehouse 72

Data Warehouse Enterprise IT Metadata 72

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

CIO Business Intelligence

MAY 24, 2022

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. Without a clear data strategy that’s aligned to their business requirements, being truly data-driven will be a challenge.

Data-driven 76

Data-driven Data Lake Data Warehouse Cost-Benefit 76

CIO Business Intelligence

SEPTEMBER 14, 2023

Data engineers also need communication skills to work across departments and to understand what business leaders want to gain from the company’s large datasets. Data engineers must also know how to optimize data retrieval and how to develop dashboards, reports, and other visualizations for stakeholders.

Analytics 128

Analytics Data Science Unstructured Data Data mining 128

AWS Big Data

NOVEMBER 8, 2023

High-quality data is not just about accuracy; it’s also about timeliness. To derive meaningful insights and ensure the optimal performance of machine learning (ML) and generative AI models, data needs to be ingested and processed in real time. With real-time streaming data, organizations can reimagine what’s possible.

Data-driven 91

Data-driven Data Lake Machine Learning Cost-Benefit 91

Cloudera

DECEMBER 21, 2020

Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. A Cloudera Data Engineering service exists. The Data Scientist.

Dashboards 97

Dashboards Visualization Data Warehouse Data Lake 97

Ontotext

MAY 2, 2024

They are expected to understand the entire data landscape and generate business-moving insights while facing the voracious needs of different teams and the constraints of technology architecture and compliance. Evolution of data approaches The data strategies we’ve had so far have led to a lot of challenges and pain points.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

CIO Business Intelligence

APRIL 25, 2022

Even organizations that understand the importance of a cohesive data strategy can find it exceedingly difficult to execute it, without getting bogged down by cross-functional team barriers and business friction and impacting time to delivery. Aligning data.

Data Architecture 88

Data Architecture Digital Transformation Data-driven Strategy 88

Cloudera

FEBRUARY 22, 2021

That benefit comes from the breadth of CDP’s analytical capabilities that translates into a unique ability to migrate different big data workloads, either from previous versions of CDH / HDP or from other cloud data warehouses and legacy on-premises data warehouses that the acquired entity might be using.

Cost-Benefit 79

Cost-Benefit Data Warehouse Data Processing Data Governance 79

AWS Big Data

JULY 28, 2023

Organizations must comply with these requests provided that there are no legitimate grounds for retaining the personal data, such as legal obligations or contractual requirements. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. We encourage you to take charge of your data privacy today.

Snapshot 86

Snapshot Metadata Measurement Data Warehouse 86

Sisense

FEBRUARY 24, 2021

CDOs who have an outward focus for collaboration are more concerned about aligning data strategy with external vendors, suppliers, and customers. Data space dimension: Traditional data vs. big data. This dimension focuses on what type of data the CDO has to wrangle.

Data Warehouse 69

Data Warehouse Big Data Metrics Visualization 69

Sisense

DECEMBER 23, 2019

AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. Once your data is prepared for analysis, the next question is: how else can AI help you? Get money out of your data. Overcoming the obstacles between you and revenue.

Data Lake 86

Data Lake Machine Learning Data Warehouse Digital Transformation 86

AWS Big Data

JUNE 23, 2023

In this post, we explain how Imperva’s solution enables users across the organization to explore, visualize, and analyze data using Amazon Redshift Serverless , Amazon Athena , and QuickSight. Challenges and needs A modern data strategy gives you a comprehensive plan to manage, access, analyze, and act on data.

Data Lake 71

Data Lake Cost-Benefit Dashboards Data Warehouse 71

CIO Business Intelligence

NOVEMBER 29, 2022

For data warehouses, it can be a wide column analytical table. Many companies reach a point where the rate of complexity exceeds the ability of data engineers and architects to support the data change management speed required for the business. Data Management

Data Architecture 92

Data Architecture Data Integration IoT Strategy 92

AWS Big Data

JANUARY 31, 2023

Amazon Redshift is a fully-managed, petabyte-scale data warehouse service in the AWS Cloud. The data sharing feature allows data owners to group databases, tables, and views in an Amazon Redshift cluster and share it with other Amazon Redshift clusters within or across AWS accounts.

Data Lake 84

Data Lake Data Governance Data Architecture Machine Learning 84