Actian

FEBRUARY 3, 2020

Why is this important you might ask, and what does it have to do with my data warehouse? Why Consolidation of the Database Market is Such a Big Deal. Customers have realized that just like digital transformation is a journey and the shift to the cloud is a journey, the evolution of databases is a journey too.

Data Warehouse 40

Data Warehouse Digital Transformation Big Data Digital 40

Sisense

APRIL 7, 2020

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. We live in an era of Big Data. The sheer amount of data being generated is greater than ever (we hit 18 zettabytes in 2018) and will continue to grow.

Big Data 86

Big Data Data Warehouse Product Management Product Management 86

Sisense

JUNE 8, 2020

Every company is becoming a data company. In Data-Powered Businesses , we dive into the ways that companies of all kinds are digitally transforming to make smarter data-driven decisions, monetize their data, and create companies that will thrive in our current era of Big Data.

Data Warehouse 89

Data Warehouse Government Digital Transformation Big Data 89

Data Pine

MAY 9, 2019

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. In a world dominated by data, it’s more important than ever for businesses to understand how to extract every drop of value from the raft of digital insights available at their fingertips.

Business Intelligence 108

Business Intelligence Business Intelligence Procurement Data Warehouse 108

Sisense

FEBRUARY 24, 2021

Data space dimension: Traditional data vs. big data. This dimension focuses on what type of data the CDO has to wrangle. Traditional datasets are often relational data found at the core of transactional services and operations: Think of an accounting system or point-of-sale system that spans multiple locations.

Chief Data Officer 69

Chief Data Officer Data Warehouse Big Data Innovation 69

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

Data Warehouse 52

Data Warehouse Data Mining Artificial Intelligence Visualization 52

Actian

AUGUST 19, 2019

IoT devices create plenty of data – much more that you might think. When you multiply this amount of data by the number of devices installed in your company’s IT ecosystem, it is apparent IoT is a truly big data challenge. Drawbacks to moving your IoT data to the cloud.

Data Warehouse 45

Data Warehouse Digital Transformation Digital Agile 45

Actian

MAY 21, 2019

In this case, actionable business insights are the finished product you are seeking to provide to your data consumers. The refinement process starts with the ingestion and aggregation of data from each of the source systems. This is often done in some sort of data warehouse. Big-Data and Real-Time insights.

Big Data 40

Big Data Data Warehouse Artificial Intelligence Digital Transformation 40

Actian

AUGUST 19, 2019

IoT devices create plenty of data – much more that you might think. When you multiply this amount of data by the number of devices installed in your company’s IT ecosystem, it is apparent IoT is a truly big data challenge. Drawbacks to moving your IoT data to the cloud.

Data Warehouse 8

Data Warehouse Digital Transformation Digital Agile 8

Sisense

APRIL 2, 2020

Every company is becoming a data company. In Data-Powered Businesses , we dive into the ways that companies of all kinds are digitally transforming to make smarter data-driven decisions, monetize their data, and create companies that will thrive in our current era of Big Data.

Vision 59

Vision Embedded Analytics Customer Experience Customer Experience 59

Actian

FEBRUARY 24, 2020

Still, the underlying premise is the same – in a post-digital transformation environment, companies need the ability to leverage a wide variety of technology components to support their business: IoT, cloud services, mobile devices, SaaS software, and traditional IT systems. RPA vendors also have a data challenge.

Digital Transformation 40

Digital Transformation Artificial Intelligence Data Warehouse Big Data 40

Sisense

APRIL 1, 2020

Our customers need to respond quickly using data and analytics, as well as AI and machine learning to make better, smarter decisions. They cannot afford to wait months building new data warehouses or IT projects. They need nimble decision-making tools and empowered data teams. We will overcome this challenge together.

Supply Chain 52

Supply Chain Healthcare Cybersecurity Data Warehouse 52

Insight Software

NOVEMBER 4, 2024

By hosting embedded analytics on Google’s cloud, application teams can keep data close to the Google tools they use every day, streamlining everything from deployment to digital transformation. Here’s what this new accessibility in Google Marketplace means for app teams and users alike. Why Choose a Cloud Marketplace?

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance IBM cost 52