IBM Big Data Hub

FEBRUARY 2, 2023

Misconception 3: All data warehouse migrations are the same, irrespective of vendors While migrating to the cloud, CTOs often feel the need to revamp and “modernize” their entire technology stack – including moving to a new cloud data warehouse vendor.

Data Warehouse 57

Data Warehouse Cost-Benefit Unstructured Data Data Architecture 57

Sisense

OCTOBER 6, 2020

Digging into quantitative data Why is quantitative data important What are the problems with quantitative data Exploring qualitative data Qualitative data benefits Getting the most from qualitative data Better together. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

JANUARY 8, 2024

Therefore, it is critical for organizations to embrace a low-latency, scalable, and reliable data streaming infrastructure to deliver real-time business applications and better customer experiences. Stream ingestion – The stream ingestion layer is responsible for ingesting data into the stream storage layer.

Analytics 111

Analytics IoT Data-driven Snapshot 111

AWS Big Data

JULY 19, 2023

We’ve seen that there is a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With this connector, you can bring the data from Google Cloud Storage to Amazon S3.

Big Data 80

Big Data Software Consulting Unstructured Data 80

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Comprehensive search and access to relevant data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 85

Data Lake Analytics Snapshot Optimization 85

Sisense

APRIL 9, 2021

The amount of data being generated and stored every day has exploded. Companies of all kinds are sitting on stockpiles of data that could someday prove valuable. Until then though, they don’t necessarily want to spend the time and resources necessary to create a schema to house this data in a traditional data warehouse.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Structured Data 52

Cloudera

JUNE 9, 2022

In the first blog of the Universal Data Distribution blog series , we discussed the emerging need within enterprise organizations to take control of their data flows. controlling distribution while also allowing the freedom and flexibility to deliver the data to different services is more critical than ever. .

Data Collection 89

Data Collection IoT Data Lake Unstructured Data 89

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

BizAcuity

APRIL 14, 2022

With the amount of data being accumulated, it is easier when said. There are a wide range of problems that are presented to organizations when working with big data. Challenges associated with Data Management and Optimizing Big Data. Unscalable data architecture. Unstructured Data Management.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Cloudera

AUGUST 13, 2021

Every enterprise is trying to collect and analyze data to get better insights into their business. Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis.

Analytics 108

Analytics Data Lake Unstructured Data Enterprise 108

Cloudera

SEPTEMBER 12, 2022

Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. And second, for the data that is used, 80% is semi- or unstructured. Both obstacles can be overcome using modern data architectures, specifically data fabric and data lakehouse.

Unstructured Data 72

Unstructured Data Data Architecture Data Lake Snapshot 72

IBM Big Data Hub

AUGUST 1, 2023

Together with data stores, foundation models make it possible to create and customize generative AI tools for organizations across industries that are looking to optimize customer care, marketing, HR (including talent acquisition) , and IT functions. models are trained on IBM’s curated, enterprise-focused data lake.

Modeling 60

Modeling Cost-Benefit Data Lake Machine Learning 60

Cloudera

JULY 26, 2021

Among the plethora of industry-specific and technology themes contributing towards that growth agenda, there are some common business and technology forces influencing data product development: An increasing focus on data collaboration partnerships between enterprises to enable data sharing and value exchange across an industry value chain.

Strategy 115

Strategy Data Science Marketing Unstructured Data 115

Sisense

JUNE 30, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways. Using visualizations to make smarter decisions.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Cloudera

SEPTEMBER 9, 2022

Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. Imagine independently discovering rich new business insights from both structured and unstructured data working together, without having to beg for data sets to be made available.

Metadata 97

Metadata Machine Learning Unstructured Data Data Lake 97

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? What are common data challenges for the travel industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Cloudera

AUGUST 21, 2020

Perhaps one of the most significant contributions in data technology advancement has been the advent of “Big Data” platforms. Historically these highly specialized platforms were deployed on-prem in private data centers to ensure greater control , security, and compliance. Streaming data analytics. . There it is.

Cost-Benefit 73

Cost-Benefit Big Data ROI Risk 73

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. let’s look at the raw product feature logs for customers in X industry paying us Y dollars).

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. When it comes to data movement outside the boundaries of Data Products (i.e., Introduction.

Metadata 122

Metadata Cost-Benefit Enterprise Interactive 122

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. What Is the Role of the Cloud in Data Modernization?

Cost-Benefit 52

Cost-Benefit Data Governance Manufacturing Data Architecture 52

Cloudera

NOVEMBER 22, 2021

Open source frameworks such as Apache Impala, Apache Hive and Apache Spark offer a highly scalable programming model that is capable of processing massive volumes of structured and unstructured data by means of parallel execution on a large number of commodity computing nodes. . CRM platforms).

Data Processing 89

Data Processing Data Warehouse Enterprise Visualization 89