IBM Big Data Hub

MARCH 29, 2024

But what if you could optimize even further? It may be the solution that finally breaks through dysfunctional silos of business units, applications, data and people, and moves beyond the constraints that have cost companies dearly. Undoubtedly.

Management 91

Management Structured Data Modeling Data Governance 91

CIO Business Intelligence

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. Structure/Operationalize. Connect/Activate.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

Smart Data Collective

JUNE 11, 2019

Big data is everywhere , and it’s finding its way into a multitude of industries and applications. One of the most fascinating big data industries is manufacturing. In an environment of fast-paced production and competitive markets, big data helps companies rise to the top and stay efficient and relevant.

Manufacturing 93

Manufacturing Analytics Big Data Data mining 93

IBM Big Data Hub

JULY 26, 2023

Discover the current and emerging use cases for AI in waste management, optimization, energy reduction and ESG reporting. Inventory optimization is important to ensure you have enough stock while also meeting customer demand. Compute optimization: Data centers consume a huge amount of electricity.By

Optimization 80

Optimization Manufacturing Cost-Benefit Reporting 80

IBM Big Data Hub

NOVEMBER 29, 2023

Furthermore, AI algorithms’ capacity for recognizing patterns—by learning from your company’s unique historical data—can empower businesses to predict new trends and spot anomalies sooner and with low latency. Here are some ways that event processing could play a pivotal role in fueling AI capabilities.

Unstructured Data 92

Unstructured Data Data-driven ROI Machine Learning 92

AWS Big Data

OCTOBER 20, 2023

We’ve seen 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 these connectors, you can bring the data from Azure Blob Storage and Azure Data Lake Storage separately to Amazon S3. Learn more in README.

Data Lake 81

Data Lake Big Data Consulting Data Warehouse 81

AWS Big Data

AUGUST 2, 2023

The workflow includes the following steps: GitHub webhook events stream data to both Amazon S3 and OpenSearch Service, facilitating real-time data analysis. A Lambda function connects to an API Gateway REST API, processing and structuring the received payloads. Want to know more?

Visualization 77

Visualization Insurance Cost-Benefit Finance 77

AWS Big Data

NOVEMBER 22, 2023

Today, we’re making available a new capability of AWS Glue Data Catalog that allows generating column-level statistics for AWS Glue tables. These statistics are now integrated with the cost-based optimizers (CBO) of Amazon Athena and Amazon Redshift Spectrum , resulting in improved query performance and potential cost savings.

Statistics 99

Statistics Data Lake Optimization Data-driven 99

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 79

Big Data Software Consulting Unstructured Data 79

Cloudera

OCTOBER 28, 2021

The German underwriters analyzed historical data such as weather, location, breed, type of crop, and a farmer’s experience to assess risk, underwrite and set price exposures. In this way, the Commercial Lines segment of insurance has really been a user of big data since its inception.

Insurance 98

Insurance Risk Unstructured Data Data-driven 98

IBM Big Data Hub

APRIL 9, 2024

” Watsonx.data lets organizations optimize workloads for different uses. Preparing and annotating data IBM watsonx.data helps organizations put their data to work, curating and preparing data for use in AI models and applications.

Management 87

Management IT Machine Learning Metrics 87

Sisense

APRIL 26, 2020

Structured vs unstructured data. Structured data is far easier for programs to understand, while unstructured data poses a greater challenge. However, both types of data play an important role in data analysis. Structured data. Structured data is organized in tabular format (ie.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

IBM Big Data Hub

JULY 19, 2023

The exponential leap in generative AI is already transforming many industries: optimizing workflows , helping human teams focus on value added tasks and accelerating time to market. Supply Chain: Demand forecasting, supply chain optimization, risk assessment and mitigation. Why IBM Consulting for generative AI on AWS?

Consulting 65

Consulting Machine Learning Manufacturing Optimization 65

IBM Big Data Hub

AUGUST 28, 2023

Data extraction Once you’ve assigned numerical values, you will apply one or more text-mining techniques to the structured data to extract insights from social media data. A targeted approach will optimize the user experience and enhance an organization’s ROI. positive, negative or neutral).

Data mining 58

Data mining Machine Learning Deep Learning Marketing 58

CDW Research Hub

APRIL 20, 2020

Snowflake, a data warehouse built specifically for the cloud, is one popular option. Snowflake helps eliminate many of the common issues data professionals face because it supports structured and semi-structured data, scales massive concurrency without limit, and boasts secure, live data sharing.

Data Warehouse 52

Data Warehouse Consulting Data-driven Structured Data 52

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Complete the implementation tasks such as data ingestion and performance testing.

Testing 96

Testing Data Warehouse Metrics Cost-Benefit 96

CIO Business Intelligence

MARCH 24, 2023

Data governance principles According to the Data Governance Institute, eight principles are at the center of all successful data governance and stewardship programs: All participants must have integrity in their dealings with each other.

Data Governance 142

Data Governance Management Metadata Data Quality 142

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. Scalable cloud solutions: The future of data and analytics.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

BizAcuity

MARCH 1, 2019

Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices. This is where AI-based analysis and response play a critical role in extracting optimal value from the data. IoT produces a treasure trove of big data.

IoT 56

IoT Internet of Things Big Data Data-driven 56

IBM Big Data Hub

JULY 5, 2022

Store and query more than just traditional structured data with multi-model capabilities. Seamlessly integrate Db2 with your existing data lake to easily query datasets residing in open data formats like Parquet, Avro and more. To learn more, visit IBM Db2 and our IBM data management page. .

Data Lake 96

Data Lake Data Warehouse Publishing Structured Data 96

Sisense

OCTOBER 6, 2020

And, as industrial, business, domestic, and personal Internet of Things devices become increasingly intelligent, they communicate with each other and share data to help calibrate performance and maximize efficiency. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company. This is quantitative data.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

JUNE 6, 2023

In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

Analytics 56

Analytics Data Lake Testing Optimization 56

AWS Big Data

JANUARY 12, 2024

Leadership and development teams can spend more time optimizing current solutions and even experimenting with new use cases, rather than maintaining the current infrastructure. With the ability to move fast on AWS, you also need to be responsible with the data you’re receiving and processing as you continue to scale.

Data Lake 91

Data Lake Cost-Benefit Visualization Structured Data 91

AWS Big Data

APRIL 20, 2023

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse.

Data Lake 73

Data Lake Data Warehouse Sales Data-driven 73

AWS Big Data

MARCH 13, 2024

This method uses GZIP compression to optimize storage consumption and query performance. You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. You’re now ready to query the tables using Athena.

Analytics 91

Analytics IoT Metadata Internet of Things 91

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. Open file formats enable analysis of the same Amazon S3 data using multiple processing and consumption layer components.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

AWS Big Data

MARCH 25, 2024

Both engines provide native ingestion support from Kinesis Data Streams and Amazon MSK via a separate streaming pipeline to a data lake or data warehouse for analysis. Data streaming also helps you optimize data pipelines by processing only the change events, allowing you to respond to data changes more quickly and efficiently.

Data Lake 87

Data Lake Unstructured Data Management Modeling 87

AWS Big Data

JULY 31, 2023

You can use AWS Glue Studio to create jobs that extract structured or semi-structured data from a data source, perform a transformation of that data, and save the result set in a data target. These jobs will load the data into the facts and dimension tables in Amazon Redshift.

Sales 52

Sales Data Warehouse Visualization Testing 52

AWS Big Data

FEBRUARY 20, 2024

Managed AWS Analytics and Database services allow for each component of the solution, from ingestion to analysis, to be optimized for speed, with little management overhead. Transactional data storage In this solution, we use Amazon DynamoDB as our transactional data store.

Visualization 96

Visualization Cost-Benefit Optimization B2B 96

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

IBM Big Data Hub

APRIL 24, 2023

Benefits of new data warehousing technology Everything is data, regardless of whether it’s structured, semi-structured, or unstructured. Most of the enterprise or legacy data warehousing will support only structured data through relational database management system (RDBMS) databases.

Data Warehouse 98

Data Warehouse Data Lake Cost-Benefit Enterprise 98

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Metadata 89

Metadata Big Data Optimization Unstructured Data 89

AWS Big Data

JANUARY 22, 2024

They classified the metrics and indicators in the following categories: Data usage – A clear understanding of who is consuming what data source, materialized with a mapping of consumers and producers. Through the lenses of the tool, Acast was able to address better monitoring, cost optimization , performance, and security.

Data-driven 83

Data-driven Advertising Metadata Data Architecture 83

AWS Big Data

OCTOBER 2, 2023

The function JSON_PARSE allows you to extract the binary data in the stream and convert it into the SUPER data type. With the SUPER data type and PartiQL language, Amazon Redshift extends its capabilities for semi-structured data analysis. In the next section, we dive into the optimal approach for deserialization.

Cost-Benefit 83

Cost-Benefit Metadata Structured Data Management 83

Sisense

MAY 11, 2021

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users. Dig into AI.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

FineReport

JUNE 24, 2021

Business intelligence can assist decision-making and operation optimization, either at the operational or tactical, or strategic levels. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. BI software solutions often support multiple data source connections.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. Although data will continue to grow at unprecedented amounts, your bottom line doesn’t need to suffer.

Data Warehouse 56

Data Warehouse Data Lake Unstructured Data Optimization 56