Data Science 101

DECEMBER 3, 2019

Building a data strategy is a great idea. It helps to avoid many of the Challenges of a Data Science Projects. General Questions Before Starting a Data Strategy. Do you have a process for solving problems involving data? What data do you collect? Technical Questions Before Starting a Data Strategy.

Data Strategy 84

Data Strategy Strategy Data Warehouse Dashboards 84

CIO Business Intelligence

FEBRUARY 14, 2023

Working with the real-time data and the features in one centralized database environment accelerates machine learning model execution. Data that takes multiple hops through databases, data warehouses, and transformations moves too slow for most real-time use cases. Artificial Intelligence, IT Leadership

Data Strategy 116

Data Strategy Strategy Machine Learning Data-driven 116

TDAN

JUNE 16, 2020

When companies embark on a journey of becoming data-driven, usually, this goes hand in and with using new technologies and concepts such as AI and data lakes or Hadoop and IoT. Suddenly, the data warehouse team and their software are not the only ones anymore that turn data […].

Data Warehouse 52

Data Warehouse Data-driven Data Lake IoT 52

TDAN

SEPTEMBER 14, 2021

Data lake is a newer IT term created for a new category of data store. But just what is a data lake? According to IBM, “a data lake is a storage repository that holds an enormous amount of raw or refined data in native format until it is accessed.” That makes sense. I think the […].

Data Lake 91

Data Lake Data Warehouse IT Data Strategy 91

Data Virtualization

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Strategy 52

Data Strategy Strategy Data Integration Management 52

Data Virtualization

MARCH 17, 2022

This growth is due to diverse data generators across consumer and enterprise landscapes, including hundreds of cloud applications, smartphones, websites, and social media networks, with each source generating. The post Don’t Drown in Redundant Data Copies.

Data Strategy 52

Data Strategy Strategy Data Integration Enterprise 52

Data Virtualization

MARCH 17, 2022

This growth is due to diverse data generators across consumer and enterprise landscapes, including hundreds of cloud applications, smartphones, websites, and social media networks, with each source generating. The post Don’t Drown in Redundant Data Copies.

Data Strategy 52

Data Strategy Strategy Data Integration Enterprise 52

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 57

Optimization Strategy Data Warehouse Cost-Benefit 57

CIO Business Intelligence

NOVEMBER 28, 2023

The knock-on impact of this lack of analyst coverage is a paucity of data about monies being spent on data management. In reality MDM ( master data management ) means Major Data Mess at most large firms, the end result of 20-plus years of throwing data into data warehouses and data lakes without a comprehensive data strategy.

Management 129

Management Data Architecture Data Lake Data Strategy 129

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

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 97

IoT Data Warehouse Internet of Things Machine Learning 97

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.

Data Warehouse 52

Data Warehouse Consulting Data-driven Structured Data 52

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

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. The user permissions are evaluated using AWS Lake Formation to filter the relevant data.

Data Governance 91

Data Governance Unstructured Data Metadata Data Lake 91

Timo Elliott

JANUARY 6, 2022

With the SAP HANA Cloud database, you can ingest live data in real time where it lives. Data is delivered in context, enabling you to make better business decisions faster. Data sense-making. Storing data isn’t enough. 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

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. Practice proper data hygiene across interfaces.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

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 98

Data Lake Sales Data Warehouse Snapshot 98

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Sisense

JANUARY 1, 2020

5 Advantages of Using a Redshift Data Warehouse. Whatever business you’re in, your company is becoming a data company. That means you need to put all that data somewhere. Chances are it’s in a data warehouse, and even better money says it’s an AWS data warehouse. Read about how Sisense BloX 2.0

Analytics 98

Analytics Digital Transformation Data Warehouse Dashboards 98

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 114

Slice and Dice Cost-Benefit Risk Data Governance 114

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. Integrating data across this hybrid ecosystem can be time consuming and expensive. The volume of data assets.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

TDAN

MARCH 19, 2019

Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years. The emergence of various new concepts, technologies, and applications such as Hadoop, Tableau, R, Power BI, or Data Lakes indicate that changes are under way.

Management 84

Management Data Lake Data Warehouse Analytics 84

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 135

Analytics Data Science Unstructured Data Data mining 135

TDAN

FEBRUARY 1, 2022

In this blog, we will discuss a common problem for data warehouses that are designed to maintain data quality and provide evidence of accuracy. Without verification, the data can’t be trusted. Enter the mundane, but necessary, task of data reconciliation. This is often a time-consuming and wasteful process.

Data Warehouse 59

Data Warehouse Data Quality IT Data Governance 59

IBM Big Data Hub

SEPTEMBER 19, 2023

How effectively and efficiently an organization can conduct data analytics is determined by its data strategy and data architecture , which allows an organization, its users and its applications to access different types of data regardless of where that data resides.

Data Science 83

Data Science Data Analytics Prescriptive Analytics Analytics 83

BizAcuity

MAY 16, 2022

For business intelligence to work out for your business – Define your data strategy roadmap. Your data strategy and roadmap will eventually lead you to a BI strategy. So, make sure you have a data strategy in place. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Cloudera

SEPTEMBER 2, 2020

Build use case-driven data applications with easy-to-use, self-serve experiences, such as Data Warehouse and Machine Learning, on CDP Private Cloud. Implement an infrastructure-agnostic enterprise hybrid cloud data strategy by incorporating CDP Private Cloud and CDP Public Cloud.

Cost-Benefit 66

Cost-Benefit Data Warehouse Data Lake Machine Learning 66

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. In this article, I’ll share insights on aligning vision and leadership, as well as reducing complexity to make data actionable for delivering real-time AI solutions.

Machine Learning 145

Machine Learning Cost-Benefit Data-driven Strategy 145

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

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 66

Data Lake Cost-Benefit Dashboards Data Warehouse 66

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?

Data Lake 86

Data Lake Machine Learning Data Warehouse Digital Transformation 86

CIO Business Intelligence

JULY 18, 2022

Data is in constant flux, due to exponential growth, varied formats and structure, and the velocity at which it is being generated. Data is also highly distributed across centralized on-premises data warehouses, cloud-based data lakes, and long-standing mission-critical business systems such as for enterprise resource planning (ERP).

Cost-Benefit 92

Cost-Benefit Data Lake Data Warehouse Enterprise 92

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

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

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 98

Dashboards Visualization Data Warehouse Data Lake 98

AWS Big Data

FEBRUARY 9, 2023

To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service (SaaS) applications. One widely used approach is getting the CRM data into your data warehouse and keeping it up to date through frequent data synchronization.

Data Warehouse 72

Data Warehouse Data-driven Snapshot Testing 72

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 78

Data Lake Data Governance Data Architecture Machine Learning 78