Sisense

OCTOBER 30, 2019

A critical part of effectively exploring your data, transforming it into actionable insights, and enhancing decision-making for your business is being empowered to slice and dice your data, and be less dependent on technical resources for new updates. Improved visibility into insights will enable you to get more out of them.

Data-driven 70

Data-driven Reporting Slice and Dice Management 70

CIO Business Intelligence

FEBRUARY 20, 2024

Manufacturers have long held a data-driven vision for the future of their industry. It’s one where near real-time data flows seamlessly between IT and operational technology (OT) systems. Legacy data management is holding back manufacturing transformation Until now, however, this vision has remained out of reach.

Data Architecture 98

Data Architecture Unstructured Data Manufacturing IT 98

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

DataKitchen

DECEMBER 20, 2020

Data-driven companies sense change through data analytics. Companies turn to their data organization to provide the analytics that stimulates creative problem-solving. The speed at which the data team responds to these requests is critical. The agility of analytics directly relates to data analytics workflows.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

AWS Big Data

APRIL 11, 2023

Such a solution should use the latest technologies, including Internet of Things (IoT) sensors, cloud computing, and machine learning (ML), to provide accurate, timely, and actionable data. To take advantage of this data and build an effective inventory management and forecasting solution, retailers can use a range of AWS services.

Forecasting 73

Forecasting Management IoT Data-driven 73

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 85

Metadata Data Lake Visualization Data Transformation 85

Cloudera

APRIL 19, 2022

Data holds incredible untapped potential for Australian organisations across industries, regardless of individual business goals, and all organisations are at different points in their data transformation journey with some achieving success faster than others. . More importantly, effective data strategies don’t stand still.

Data-driven 89

Data-driven Data Strategy Strategy Big Data 89

InsightOut

MAY 4, 2021

In this data-driven world, building a team of data analysts can be a challenge. Implementing data visualization and analytics dashboards can be the beginning of the data transformation journey.

Visualization 52

Visualization Dashboards Data-driven Data Transformation 52

datapine

MAY 2, 2023

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications. Did you know?

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

Octopai

JUNE 22, 2023

In the era of big data, organizations are grappling with the challenge of effectively managing and leveraging vast amounts of data. Two prominent approaches have emerged: self-service data management and centralized data management. This approach offers greater control and reduces the risk of data inconsistencies.

Management 52

Management Data-driven Data Quality Data Governance 52

CIO Business Intelligence

JANUARY 24, 2024

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

AWS Big Data

APRIL 26, 2023

Additionally, this forecasting system needs to provide data enrichment steps including byproducts, serve as the master data around the semiconductor management, and enable further use cases at the BMW Group. To enable this use case, we used the BMW Group’s cloud-native data platform called the Cloud Data Hub.

Manufacturing 119

Manufacturing Forecasting Data Lake Big Data 119

erwin

APRIL 29, 2020

Data lineage is the journey data takes from its creation through its transformations over time. Tracing the source of data is an arduous task. With all these diverse data sources, and if systems are integrated, it is difficult to understand the complicated data web they form much less get a simple visual flow.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

AWS Big Data

APRIL 19, 2023

Data mesh is a new approach to data management. Companies across industries are using a data mesh to decentralize data management to improve data agility and get value from data. This is especially true in a large enterprise with thousands of data products.

Technology 79

Technology Data-driven Machine Learning Sales 79

erwin

JUNE 29, 2021

From overburdened data operations experts enabling data usage, to end-users struggling to access the data that matters, organizations continue to look for ways to give stakeholders the tools they need to do their jobs more effectively. A key trend proving successful in data empowerment is investing in self-service technology.

Data Governance 64

Data Governance Data-driven Reporting Technology 64

Sisense

FEBRUARY 26, 2020

We all know that data is becoming more and more essential for businesses, as the volume of data keeps growing. Dresner reported that nearly 97% of respondents in their Big Data Analytics Market Study consider Big Data to be either important or critical to their businesses. Become data-driven to succeed.

Digital Transformation 90

Digital Transformation Analytics Cost-Benefit Data-driven 90

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Don’t try to do everything at once!

Data Governance 83

Data Governance Business Objectives Strategy Data Quality 83

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 83

Management Data Warehouse Digital Transformation Dashboards 83

Cloudera

JULY 9, 2021

If you’ve followed Cloudera for a while, you know we’ve long been singing the praises—or harping on the importance, depending on perspective—of a solid, standalone enterprise data strategy. The ways data strategies are implemented, the resulting outcomes and the lessons learned along the way provide important guardrails.

Data Strategy 109

Data Strategy Strategy Data-driven Machine Learning 109

Sisense

AUGUST 28, 2020

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. What is data integrity? Data integrity risks.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

AWS Big Data

JUNE 6, 2023

Alerts and notifications play a crucial role in maintaining data quality because they facilitate prompt and efficient responses to any data quality issues that may arise within a dataset. It simplifies your experience of monitoring and evaluating the quality of your data.

Data Quality 71

Data Quality Metrics Data-driven Visualization 71

Alation

FEBRUARY 20, 2020

The energy at the conference was amazing – over 2,000 attendees and 100 vendors gathered to find our inner data heroes. And the Great BI Bake-Off is a perfect example: Four vendors (selected by their Gartner search popularity) took the stage in a live showdown of data viz expertise. Rita Sallam Introduces the Data Prep Rodeo.

Scorecard 52

Scorecard ROI Data-driven Visualization 52

Cloudera

DECEMBER 21, 2021

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. Data pipelines are composed of multiple steps with dependencies and triggers.

Snapshot 116

Snapshot Data-driven Optimization Management 116

erwin

SEPTEMBER 17, 2020

Replace manual and recurring tasks for fast, reliable data lineage and overall data governance. It’s paramount that organizations understand the benefits of automating end-to-end data lineage. The importance of end-to-end data lineage is widely understood and ignoring it is risky business. Doing Data Lineage Right.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Anmut

MARCH 24, 2022

A closer look at the importance (and transformational value) of your organisation’s data landscape. After decades in the background, data is currently king of the business world. Over 70% of digital transformations fail, and most CDOs last less than two-and-half years. What is a data landscape?

ROI 52

ROI Measurement Data-driven Data Transformation 52

bridgei2i

NOVEMBER 17, 2020

But what is changing today, is the nature and shape of data powering these systems and processes. A variety of signals in the new digital world can be transformed into data to derive insights and learnings on how to improve process performance. Automation through technology had the same outcomes as the first wave though.

Deep Learning 85

Deep Learning Manufacturing Optimization Data-driven 85

Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

AWS Big Data

MAY 16, 2023

Different communication infrastructure types such as mesh network and cellular can be used to send load information on a pre-defined schedule or event data in real time to the backend servers residing in the utility UDN (Utility Data Network).

Dashboards 74

Dashboards Statistics Data Collection Business Intelligence 74

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. So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

OCTOBER 12, 2023

You can run analytics workloads at any scale with automatic scaling that resizes resources in seconds to meet changing data volumes and processing requirements. AWS Step Functions is a serverless orchestration service that enables developers to build visual workflows for applications as a series of event-driven steps.

Big Data 103

Big Data Data-driven Management Visualization 103

AWS Big Data

APRIL 25, 2024

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

Optimization 65

Optimization Data Lake Cost-Benefit Reporting 65

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. In this post, we focus on data migration and ongoing transformation.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

Alation

FEBRUARY 2, 2023

Data product managers are in high demand these days. This makes it more important for aspiring data product managers to stay ahead of the competition. So what sets data product managers apart from the pack? This post will unpack the top 7 traits that successful data product managers have in common. Sounds exciting?

Management 52

Management Data-driven Visualization Strategy 52

Cloudera

MARCH 14, 2023

We just announced the general availability of Cloudera DataFlow Designer , bringing self-service data flow development to all CDP Public Cloud customers. In this blog post we will put these capabilities in context and dive deeper into how the built-in, end-to-end data flow life cycle enables self-service data pipeline development.

Testing 81

Testing Publishing Metadata Interactive 81

Cloudera

JUNE 1, 2021

This means we can double down on our strategy – continuing to win the Hybrid Data Cloud battle in the IT department AND building new, easy-to-use cloud solutions for the line of business. It also means we can complete our business transformation with the systems, processes and people that support a new operating model. .

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

Alation

MARCH 22, 2022

Data people face a challenge. They must put high-quality data into the hands of users as efficiently as possible. As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

AWS Big Data

JANUARY 17, 2024

This allows you to simplify security and governance over transactional data lakes by providing access controls at table-, column-, and row-level permissions with your Apache Spark jobs. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 90

Data Lake Snapshot Big Data Data-driven 90