AWS Big Data

FEBRUARY 7, 2023

Business needs often drive table structure, such as schema evolution (the addition of new columns, removal of existing columns, update of column names, and so on) for some of these tables in one business function that requires other business functions to replicate the same. You don’t alter queries separately in the data lake.

Data Lake 74

Data Lake Testing Big Data Structured Data 74

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

Cloudera

DECEMBER 11, 2020

Without meeting GxP compliance, the Merck KGaA team could not run the enterprise data lake needed to store, curate, or process the data required to inform business decisions. It established a data governance framework within its enterprise data lake. Driving innovation with secure and governed data .

Data Lake 98

Data Lake Cost-Benefit Unstructured Data Data Governance 98

CIO Business Intelligence

DECEMBER 4, 2023

Operationalizing data to drive revenue CIOs report that their roles are rising in importance and impact. A modern information lifecycle management approach Today’s ILM approach recognizes the enterprise value of all digitized and enriched assets , avoiding the habituated, narrow reliance ontraditional structured data.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

AWS Big Data

NOVEMBER 9, 2023

Flat files – Other systems supply data in the form of flat files of different formats. These files, stored in an SFTP location, might contain records, reports, logs, or other kinds of raw data that can be further processed and analyzed. AWS Glue – AWS Glue is used to load files into Amazon Redshift through the S3 data lake.

Data Warehouse 108

Data Warehouse Testing Data Quality Reporting 108

CIO Business Intelligence

OCTOBER 25, 2023

The release of intellectual property and non-public information Generative AI tools can make it easy for well-meaning users to leak sensitive and confidential data. Once shared, this data can be fed into the data lakes used to train large language models (LLMs) and can be discovered by other users.

Enterprise 133

Enterprise Risk Manufacturing Finance 133

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. 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. It consists of full-day and intraday tables.

Analytics 56

Analytics Data Lake Testing Optimization 56

AWS Big Data

MARCH 28, 2023

As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 72

Data Lake Testing Snapshot Sales 72

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

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. Getting started with AWS SCT is a straightforward process. Also, consider following the best practices for AWS SCT.

Testing 101

Testing Data Warehouse Metrics Cost-Benefit 101

IBM Big Data Hub

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. Similarly, the relational database has been the foundation for data warehousing for as long as data warehousing has been around.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

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 83

Big Data Software Consulting Unstructured Data 83

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

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 78

Data Lake Data Warehouse Sales Data-driven 78

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

BizAcuity

MARCH 1, 2019

Data is only useful when it is actionable for which it needs to be supplemented with context and creativity. 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. and constantly report this data to backend.

IoT 56

IoT Internet of Things Big Data Data-driven 56

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. Additionally, data is extracted from vendor APIs that includes data related to product, marketing, and customer experience.

Data Warehouse 94

Data Warehouse Data Lake Analytics Data Science 94

IBM Big Data Hub

APRIL 24, 2023

Why data warehousing is critical to a company’s success Data warehousing is the secure electronic information storage by a company or organization. It creates a trove of historical data that can be retrieved, analyzed, and reported to provide insight or predictive analysis into an organization’s performance and operations.

Data Warehouse 97

Data Warehouse Data Lake Cost-Benefit Enterprise 97

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

AWS Big Data

APRIL 19, 2023

Every day, customers are challenged with how to manage their growing data volumes and operational costs to unlock the value of data for timely insights and innovation, while maintaining consistent performance. As data workloads grow, costs to scale and manage data usage with the right governance typically increase as well.

Data Warehouse 56

Data Warehouse Data Lake Unstructured Data Optimization 56

CIO Business Intelligence

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. Lakehouses redeem the failures of some data lakes.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

CIO Business Intelligence

OCTOBER 18, 2022

She decided to bring Resultant in to assist, starting with the firm’s strategic data assessment (SDA) framework, which evaluates a client’s data challenges in terms of people and processes, data models and structures, data architecture and platforms, visual analytics and reporting, and advanced analytics.

Data Transformation 141

Data Transformation Consulting Data Lake Reporting 141

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

CIO Business Intelligence

APRIL 4, 2023

A complex data landscape prevents data scientists and data engineers from easily linking the right data together at the right time. Additionally, multiple systems of record create a confusing environment when those sources do not report the same answers. Tolkien intimated, anything worth achieving takes time.

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. Pillar 3: Analytics The analytics pillar defines capabilities that help you generate insights on top of your customer data. Organizations using C360 achieved 43.9% faster time to market, and 19.1%

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

AWS Big Data

OCTOBER 2, 2023

JSON data in Amazon Redshift Amazon Redshift enables storage, processing, and analytics on JSON data through the SUPER data type, PartiQL language, materialized views, and data lake queries. The function JSON_PARSE allows you to extract the binary data in the stream and convert it into the SUPER data type.

Cost-Benefit 88

Cost-Benefit Metadata Structured Data Management 88

CDW Research Hub

DECEMBER 4, 2019

Cloud-based data warehouses can also perform complex analytical queries much faster due to the use of massively parallel processing (MPP), which uses multiple processors—each with its own operating system and memory—to simultaneously perform a set of coordinated computations.

Data Warehouse 52

Data Warehouse Data mining Data Lake Dashboards 52

FineReport

APRIL 11, 2023

Every user can now create interactive reports and utilize data visualization to disseminate knowledge to both internal and external stakeholders. BI dashboards typically display a variety of data visualizations to give users a comprehensive view of relevant KPIs and trends for both strategic planning and operational decision-making.

Dashboards 40

Dashboards Business Intelligence Cost-Benefit Metrics 40

Sisense

JUNE 30, 2020

The data drawn from power visualizations comes from a variety of sources: Structured data , in the form of relational databases such as Excel, or unstructured data, deriving from text, video, audio, photos, the internet and smart devices. Visual analytics and data visualizations in action.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Cloudera

JULY 26, 2021

Auditabily: Data security and compliance constituents need to understand how data changes, where it originates from and how data consumers interact with it. a technology choice such as Spark Streaming is overly focused on throughput at the expense of latency) or data formats (e.g., data warehousing).

Strategy 115

Strategy Data Science Marketing Unstructured Data 115

Corinium

APRIL 25, 2019

In data-driven organizations, data is flowing. It is being aggregated from various transactional systems into data masters or data lakes, being analysed, being distributed to downstream users or even 3rd-parties, reported on, exported to Excel, attached to emails, you name it, data is being shared across silos.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Sisense

MAY 11, 2021

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. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021! Enriching (e.g.,

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

JUNE 21, 2023

The challenge comes when we need to ask more complex questions of our data, for example, what was the year-on-year quarterly sales growth by product broken down by country? The case for a data warehouse A data warehouse is ideally suited to answer OLAP queries. To house our data, we need to define a data model.

Data Warehouse 81

Data Warehouse Data Lake OLAP Cost-Benefit 81

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 122

Metadata Cost-Benefit Enterprise Interactive 122