Cloudera

SEPTEMBER 29, 2022

Data teams have the impossible task of delivering everything (data and workloads) everywhere (on premise and in all clouds) all at once (with little to no latency). Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. Data mesh defined.

Data Architecture 74

Data Architecture Metadata Data Warehouse Sales 74

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. Three Types of Metadata in a Data Catalog.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

Ontotext

MAY 2, 2024

Data leaders today are faced with an almost impossible challenge. 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.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Cloudera

DECEMBER 21, 2023

How long would it take you to find the data you need to even begin to come up with a data-driven response? Creating a query when you’ve new to a data model Whether you’re new to a role, or just new to a given data source, finding data is 90 percent of the query creation problem.

Optimization 67

Optimization Sales Data Warehouse Measurement 67

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data discovery tools available in the market to take their brand forward.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

datapine

JANUARY 24, 2021

In our cutthroat digital age, the importance of setting the right data analysis questions can define the overall success of a business. That being said, it seems like we’re in the midst of a data analysis crisis. Your Chance: Want to perform advanced data analysis with a few clicks? Data Is Only As Good As The Questions You Ask.

IT 317

IT Statistics KPI Data-driven 317

erwin

MAY 2, 2022

How to create a solid foundation for data modeling of OLTP systems. As you undertake a cloud database migration , a best practice is to perform data modeling as the foundation for well-designed OLTP databases. This makes mastering basic data modeling techniques and avoiding common pitfalls imperative. Data modeling basics.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

Smart Data Collective

APRIL 29, 2020

As the world is gradually becoming more dependent on data, the services, tools and infrastructure are all the more important for businesses in every sector. Data management has become a fundamental business concern, and especially for businesses that are going through a digital transformation. What is data management?

Management 84

Management Data Warehouse Digital Transformation Dashboards 84

Cloudera

MAY 17, 2021

CDP (Cloudera Data Platform) Private Cloud 1.2 In this blog, we’ll cover the complete range of new capabilities and updates for CDP Private Cloud as a whole (the platform) as well as for both the CDW (Cloudera Data Warehouse) and CML (Cloudera Machine Learning) services. release blog ). Platform – In-place Updates.

Machine Learning 89

Machine Learning Data Warehouse Data-driven Metrics 89

CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering. Know how to handle your data.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

erwin

APRIL 2, 2021

Organizations are managing more data than ever. With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Who is authorized to use it and how?

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

CIO Business Intelligence

NOVEMBER 23, 2022

The process is driven by a “comprehensive picture of an entire enterprise from the perspectives of owner, designer, and builder,” according to the EABOK. Unlike other frameworks, EA doesn’t include a formal documentation structure; instead, it’s intended to offer a more holistic view of the enterprise. Data warehouse.

Enterprise 128

Enterprise Cost-Benefit Digital Transformation Strategy 128

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. A sample data warehousing project.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

In(tegrate) the Clouds

JUNE 23, 2016

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses. Integration is event-based rather than clock-driven.

Data Integration 49

Data Integration Data Lake Data Warehouse Data-driven 49

erwin

OCTOBER 31, 2019

Do you know where your data is? What data you have? Add to the mix the potential for a data breach followed by non-compliance, reputational damage and financial penalties and a real horror story could unfold. s Information Commissioner’s Office had levied against both Facebook and Equifax for their data breaches.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

Smart Data Collective

APRIL 15, 2021

Business Intelligence is the practice of collecting and analyzing data and transforming it into useful, actionable information. Business Intelligence uses methods and tools like machine learning to take massive, unstructured swaths of data and turn them into easy-to-use reports. Set Up Data Integration. Pitch to Key Players.

Business Intelligence 97

Business Intelligence Analytics Statistics Data Warehouse 97

Cloudera

JULY 11, 2023

Apache Impala and Apache Kudu make a great combination for real-time analytics on streaming data for time series and real-time data warehousing use cases. Cloudera offers Apache Kudu to run in Real Time DataMart Clusters , and Apache Impala to run in Kubernetes in the Cloudera Data Warehouse form factor. 20 or higher.

Data Warehouse 70

Data Warehouse Data-driven Reporting Analytics 70

AWS Big Data

MARCH 7, 2024

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. 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. We think of this concept as inside-out data movement. Example Corp.

Data Lake 116

Data Lake Analytics Dashboards Metrics 116

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Jet Global

APRIL 19, 2021

Executives increasingly rely on data and advanced analytics to make business decisions. They also need the ability to access and parse that data faster and in more creative ways. Meanwhile, the data that businesses have access to and the number of systems producing that data are growing at lightspeed.

Data Warehouse 98

Data Warehouse Cost-Benefit OLAP Business Intelligence 98

Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. But governance is a time-consuming process (for users and data stewards alike).

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

Darkhorse

DECEMBER 11, 2017

The chasm between Business and IT is well documented and has existed since the first punch-card mainframe dimmed the lights of MIT to solve the ballistic trajectory of WWII munitions. Analytics and now Data Science are trapped in the middle. A recent HBR article put it at 100% for data science projects. That’s abysmal.

Analytics 80

Analytics Visualization Data Warehouse Data-driven 80

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

MAY 16, 2024

In this post, we discuss how Amazon Redshift spatial index functions such as Hexagonal hierarchical geospatial indexing system (or H3) can be used to represent spatial data using H3 indexing for fast spatial lookups at scale. Navigating the vast landscape of data-driven insights has always been an exciting endeavor.

Data Warehouse 82

Data Warehouse Visualization Cost-Benefit Optimization 82

AWS Big Data

MARCH 20, 2024

As your organization becomes more data driven and uses data as a source of competitive advantage, you’ll want to run analytics on your data to better understand your core business drivers to grow sales, reduce costs, and optimize your business. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 125

Data Warehouse Business Driver Data Lake Data-driven 125

Cloudera

NOVEMBER 25, 2020

The challenges Matthew and his team are facing are mainly about access to a multitude of data sets, of various types and sources, with ease and ad-hoc, and their ability to deliver data-driven and confident outcomes. . Most of their research data is unstructured and has a lot of variety. Challenges Ahead.

Data Warehouse 58

Data Warehouse Unstructured Data Analytics Visualization 58

BI-Survey

AUGUST 21, 2020

Data warehousing is getting on in years. However, data warehousing and BI applications are only considered moderately successful. Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. Can the basic nature of the data be proactively improved?

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 82

Data Lake Data Warehouse Data-driven Optimization 82

Alation

JANUARY 17, 2023

Chances are, you’ve heard of the term “modern data stack” before. In this article, I will explain the modern data stack in detail, list some benefits, and discuss what the future holds. What Is the Modern Data Stack? It is known to have benefits in handling data due to its robustness, speed, and scalability.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data Discovery tools available in the market to take their brand forward.

Business Intelligence 20

Business Intelligence Knowledge Discovery Unstructured Data Software 20

IBM Big Data Hub

MARCH 25, 2022

A database is a crucial engine for a world becoming more data driven. Businesses are more heavily relying on smart insights and emerging patterns to succeed. Advancements in software and hardware had an interplay between the rising appetite for any organization making a data-driven decision.

Data-driven 78

Data-driven Data Warehouse Data Processing Marketing 78

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. roll-ups of many rows of data). As the name suggests, a common use case for this is any transactional data. So let’s dive in! OLTP vs OLAP.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

AWS Big Data

JULY 25, 2023

Today, in order to accelerate and scale data analytics, companies are looking for an approach to minimize infrastructure management and predict computing needs for different types of workloads, including spikes and ad hoc analytics. This is a guest post co-written with Cameron Davie from Talend.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks. Greg Rahn: Sure.

Data Warehouse 42

Data Warehouse Marketing Big Data Data Lake 42

Cloudera

AUGUST 30, 2022

Data is the fuel that drives government, enables transparency, and powers citizen services. It outlines a scenario in which “recently married people might want to change their names on their driver’s licenses or other documentation. Data quality issues deter trust and hinder accurate analytics. Modern data architectures.

Data Architecture 77

Data Architecture Data Lake Metadata Data Warehouse 77