Smart Data Collective

JUNE 7, 2019

This is where real-time stream processing enters the picture, and it may probably change everything you know about big data. Read this article as we’ll tackle what big data and stream processing are. We’ll also deal with how big data stream processing can help new emerging markets in the world.

Big Data 202

Big Data Real-time Data Data Warehouse Innovation 202

Smart Data Collective

MAY 31, 2022

Big data technology is having a huge impact on the state of modern business. The technology surrounding big data has evolved significantly in recent years, which means that smart businesses will have to take steps to keep up with it. What is Data Activation? It Started Reverse ETL.

Data Warehouse 331

Data Warehouse Big Data Customer Experience Customer Experience 331

Smart Data Collective

APRIL 8, 2020

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. Big data and data warehousing.

Data Warehouse 331

Data Warehouse Big Data Business Intelligence Business Intelligence 331

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 Supply Chain Data Warehouse Data Analytics 52

Dataversity

DECEMBER 14, 2020

It was only a few years ago that BI and data experts excitedly claimed that petabytes of unstructured data could be brought under control with data pipelines and orderly, efficient data warehouses. But as big data continued to grow and the amount of stored information increased every […].

Data Warehouse 147

Data Warehouse Big Data Data Architecture Data Management 147

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. What Database Market Consolidation Means for Your Data Warehouse. The consolidation of the database market has a few key impacts relative to your data warehouse.

Data Warehouse 40

Data Warehouse Digital Transformation Big Data Digital 40

Smart Data Collective

JUNE 15, 2021

It’s also possible to employ extra caching or materialized views in the data warehouse in addition to caching in Looker (depending on the capability of your data warehouse). One added tip is to aggregate your data before loading it into Looker or in the data warehouse to reduce the amount of data loaded onto the platform.

Data Warehouse 239

Data Warehouse User Experience Big Data 239

Smart Data Collective

NOVEMBER 18, 2020

The Bureau of Labor Statistics estimates that the number of data scientists will increase from 32,700 to 37,700 between 2019 and 2029. Unfortunately, despite the growing interest in big data careers, many people don’t know how to pursue them properly. Data Mining is an important research process.

Data Mining 356

Data Mining Big Data Artificial Intelligence Data Warehouse 356

Sisense

MARCH 20, 2019

To do that, a data engineer needs to be skilled in a variety of platforms and languages. In our never-ending quest to make BI better, we took it upon ourselves to list the skills and tools every data engineer needs to tackle the ever-growing pile of Big Data that every company faces today. Data Warehousing.

Big Data 72

Big Data IBM Maintenance IBM Support Data Warehouse 72

Actian

JULY 26, 2019

So, you have made the business case to modernize your data warehouse. But how do you effectively go about choosing the right data warehouse to migrate to? Should you stay with your existing traditional data warehouse provider as they try to convince you to stay on-premise with their latest appliance?

Data Warehouse 40

Data Warehouse Government Predictive Analytics Banking 40

Astera

FEBRUARY 26, 2024

Azure SQL Data Warehouse, now called Azure Synapse Analytics, is a powerful analytics and BI platform that enables organizations to process and analyze large volumes of data in a centralized place. However, this data is often scattered across different systems, making it difficult to consolidate and utilize effectively.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data Documentation 52

Astera

NOVEMBER 30, 2023

With its foundation rooted in scalable hub-and-spoke architecture, Data Vault 1.0 provided a framework for traceable, auditable, and flexible data management in complex business environments. Building upon the strengths of its predecessor, Data Vault 2.0 What’s New in Data Vault 2.0? Data Vault 2.0 Data Vault 2.0

Data Warehouse 52

Data Warehouse Healthcare Big Data Data Governance 52

Astera

DECEMBER 16, 2022

John Stillwagen, Senior Director MIS at La Jolla Institute for Immunology, demonstrated how efficiently our data warehouse solution, Astera Data Warehouse Builder, helps you build an enterprise-grade data warehouse via a no-code interface. Big Data LDN 2022 | Olympia, London.

Data Warehouse 59

Data Warehouse Big Data Data Management Documentation 59

Smart Data Collective

MARCH 30, 2022

Azure Data Lake Storage Gen2 is based on Azure Blob storage and offers a suite of big data analytics features. If you don’t understand the concept, you might want to check out our previous article on the difference between data lakes and data warehouses.

Data Warehouse 250

Data Warehouse Big Data Data Analytics Data Analytics 250

Astera

APRIL 27, 2023

The modern data stack (MDS) is a collection of tools for data integration that enable organizations to collect, process, store and analyze data. Being based on a well-integrated cloud platform, modern data stack offers scalability, efficiency, and proficiency in data handling.

Data Warehouse 52

Data Warehouse Big Data Cloud Computing Data Analytics 52

Astera

MAY 9, 2023

Automated data processing solutions, such as computer software programming, play a significant role in this. It can help turn large amounts of data, including big data, into meaningful insights for quality management and decision-making. Interested in Learning More About Cloud Data Integration?

Data Warehouse 52

Data Warehouse Big Data Innovation Artificial Intelligence 52

Tableau

JUNE 8, 2021

In many of the conversations we have with IT and business leaders, there is a sense of frustration about the speed of time-to-value for big data and data science projects. We often hear that organizations have invested in data science capabilities but are struggling to operationalize their machine learning models.

Innovation 91

Innovation Data Warehouse Data Architecture Visualization 91

Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. This is also true that decentralized data management is not new.

Data Management 162

Data Management Government Data Warehouse Big Data 162

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Data Management 211

Data Management Data Warehouse Master Data Management Digital Transformation 211

BizAcuity

MAY 16, 2022

To stay relevant in the market and to increase brand awareness, organizations use big data analytics and business intelligence to navigate their way after getting a full understanding of their ideal customers and their behavior before and during the buying journey. Data mining.

Business Intelligence 130

Business Intelligence Business Intelligence Data Mining Data Warehouse 130

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

Digital Transformation 98

Digital Transformation Data Warehouse Embedded Analytics Artificial Intelligence 98

Dataversity

FEBRUARY 18, 2022

Even as we grow in our ability to extract vital information from big data, the scientific community still faces roadblocks that pose major data mining challenges. In this article, we will discuss 10 key issues that we face in modern data mining and their possible solutions.

Data Mining 130

Data Mining Big Data Data Warehouse Data Visualization 130

Astera

JANUARY 13, 2023

For decades, organizations have used Extract, transform and load (ETL) to integrate data stored across disparate source systems. However, the increasing data volume, variety, and velocity, presented by the big data age makes the traditional ETL approach inefficient in many cases. ELT in the Era of Cloud.

Data Warehouse 52

Data Warehouse Data Management Big Data Business Intelligence 52

Sisense

APRIL 17, 2020

In Monetizing Your Data , we look at digital transformation: the ways of turning data into new revenue streams and apps that boost income, increase stickiness, and help your company thrive in the world of Big Data. You can do these smaller experiments more cost-efficiently, saving money over the traditional data strategy.

Digital Transformation 81

Digital Transformation Data Warehouse Innovation Digital 81

Actian

FEBRUARY 6, 2020

Stream data integration is the way you do that. The Exciting Challenge of Big Data. For nearly a decade, analysts and industry experts have been talking about Big Data and the impact that it was going to have on organizations. Big data isn’t an “emerging trend’ anymore – it’s a business reality.

Data Warehouse 40

Data Warehouse Supply Chain Real-time Data Big Data 40

Sisense

APRIL 2, 2020

How to Choose a Database to Solve Your Data Challenges. There’s more to life on the data team than just SQL. A wide variety of modern databases have arisen to tackle the challenges of Big Data, taking a variety of forms, each suited for different kinds of data and tasks.

Data Warehouse 83

Data Warehouse Embedded Analytics Big Data 83

Tableau

JUNE 8, 2021

In many of the conversations we have with IT and business leaders, there is a sense of frustration about the speed of time-to-value for big data and data science projects. We often hear that organizations have invested in data science capabilities but are struggling to operationalize their machine learning models.

Innovation 52

Innovation Data Warehouse Data Architecture Visualization 52

Actian

JUNE 10, 2019

This includes both ready-to-use SaaS solutions as well as cloud-based infrastructure (IaaS and Paas) for various needs, such as data warehouses and in-house developed applications. Data warehouse migration to the cloud. During the past few years, Hadoop has been the big trend in data warehousing.

Data Management 40

Data Management Data Warehouse Big Data Data Governance 40

Astera

MARCH 16, 2023

For a long time, databases have been the go-to avenue for companies to store and access data. However, with the rise of big data, businesses of all sizes are rapidly adopting cloud data lakes as a cheaper yet highly scalable alternative storage solution. hosted in its public cloud, Azure.

Big Data 52

Big Data Data Warehouse Data Quality Data Analytics 52

Smart Data Collective

APRIL 15, 2021

Set Up Data Integration. Data warehouses, a database that keeps the information in a processed and defined format, cannot connect directly to information sources, so data integration tools must process the raw data ahead of time to allow it to be usable. Laying out these components will be helpful down the line.

Business Intelligence 242

Business Intelligence Business Intelligence Data Warehouse Documentation 242

Astera

OCTOBER 27, 2023

What is a Cloud Data Warehouse? Simply put, a cloud data warehouse is a data warehouse that exists in the cloud environment, capable of combining exabytes of data from multiple sources. A cloud data warehouse is critical to make quick, data-driven decisions.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

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

Sisense

JUNE 8, 2020

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. Datasets are on the rise and most of that data is on the cloud.

Data Warehouse 89

Data Warehouse Government Digital Transformation Big Data 89

Sisense

JANUARY 13, 2020

From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. And cloud data warehouses or data lakes give companies the capability to store these vast quantities of data. How data enhances product development.

Supply Chain 52

Supply Chain Embedded Analytics Pharmaceutical Data Warehouse 52

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Big Data Ecosystem.

Big Data 130

Big Data Data Analytics Data Analytics Data Management 130

ElegantJ BI

JUNE 17, 2015

Since I couldn’t be in two places at the same time, I tried to make the choices that were most relevant to our team, our customers and our partners, and I chose the following sessions.

Business Intelligence 130

Business Intelligence Business Intelligence Data Warehouse Data Discovery 130

ElegantJ BI

JUNE 17, 2015

Since I couldn’t be in two places at the same time, I tried to make the choices that were most relevant to our team, our customers and our partners, and I chose the following sessions.

Business Intelligence 130

Business Intelligence Business Intelligence Data Warehouse Data Discovery 130