Astera

APRIL 7, 2023

Finally, the stored data is retrieved at optimal speeds to support efficient analysis and decision-making. Essentially, a data warehouse also acts as a centralized database for storing structured, analysis-ready data and giving a holistic view of this data to decision-makers.

Data Warehouse 52

Data Warehouse Healthcare Data Management Data Quality 52

Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

BizAcuity

AUGUST 1, 2022

JasperSoft for Big Data Analytics. Jaspersoft is particularly resourceful as a cost-effective big data analytics solution that can connect with and present information for Cassandra Analytics, MongoDB Analytics, Hadoop Analytics, among many others. [Source: [link] ].

IBM Support 130

IBM Support IBM cost IBM Maintenance Big Data 130

Sisense

JULY 8, 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. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Embedded Analytics Real-time Data Documentation 90

Astera

MAY 31, 2024

Data Science vs. Data Analytics Organizations increasingly use data to gain a competitive edge. Two key disciplines have emerged at the forefront of this approach: data science vs data analytics. In contrast, data science enables you to create data-driven algorithms to forecast future outcomes.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

Actian

OCTOBER 29, 2019

When it comes to data management and data warehouse solutions, right now is the best time to move forward on modernization. Legacy data warehouse systems are aging. Modern data warehouse solutions are mainstream tech. Data warehousing and analytics aren’t just about the warehouse.

Data Warehouse 40

Data Warehouse Digital Transformation Digital Finance 40

Analysts Corner

JUNE 18, 2023

ETL Developer: Defining the Role An ETL developer is a professional responsible for designing, implementing, and managing ETL processes that extract, transform, and load data from various sources into a target data store, such as a data warehouse. Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Actian

JUNE 4, 2019

Implementing a data warehouse is a big investment for most companies and the decisions you make now will impact both your IT costs and the business value you are able to create for many years. Data Warehouse Cost. Your data warehouse is the centralized repository for your company’s data assets.

Data Warehouse 40

Data Warehouse Digital Transformation Data Quality Data Modelling 40

Astera

MAY 30, 2024

What Is Data Analytics? Data analytics is the science of analyzing raw data to draw conclusions about it. The process involves examining extensive data sets to uncover hidden patterns, correlations, and other insights. Data Mining : Sifting through data to find relevant information.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Data Pine

OCTOBER 25, 2022

With ‘big data’ transcending one of the biggest business intelligence buzzwords of recent years to a living, breathing driver of sustainable success in a competitive digital age, it might be time to jump on the statistical bandwagon, so to speak. of all data is currently analyzed and used. click for book source**.

Business Intelligence 117

Business Intelligence Business Intelligence Big Data Data Mining 117

Inflexion Analytics

JULY 23, 2021

Managing your farm without monitoring everything you do is like driving a car with a blindfold. But, whereas once you might have relied on a closeness and understanding of the land to assess yields and predict your productivity, now we have data. For crop spreading, spraying and monitoring, we’re seeing an increasing use of drones.

Big Data 52

Big Data Data Analytics Data Analytics Data Warehouse 52

Tableau

APRIL 18, 2022

Review quality and structural information on data and data sources to better monitor and curate for use. Surface robust metadata where users need it most across their analytics journey, while ensuring bilateral communication with enterprise tooling. Data quality and lineage. Data integration. Orchestration.

Data Quality 102

Data Quality Government Artificial Intelligence Data Warehouse 102

Tableau

APRIL 18, 2022

Review quality and structural information on data and data sources to better monitor and curate for use. Surface robust metadata where users need it most across their analytics journey, while ensuring bilateral communication with enterprise tooling. Data quality and lineage. Data integration. Orchestration.

Data Quality 98

Data Quality Government Artificial Intelligence Data Warehouse 98

Data Pine

JANUARY 24, 2021

But if you find a development opportunity, and see that your business performance can be significantly improved, then a KPI dashboard software could be a smart investment to monitor your key performance indicators and provide a transparent overview of your company’s data. Now, with Data Dan, you only get to ask him three questions.

Data Visualization 126

Data Visualization Data Analytics Data Analytics Data Quality 126

The BAWorld

SEPTEMBER 18, 2024

Load : The formatted data is then transferred into a data warehouse or another data storage system. ELT (Extract, Load, Transform) This method proves to be efficient when both your data source and target reside within the same ecosystem. Extract: Data is pulled from its source.

Data Warehouse 52

Data Warehouse Finance Data Architecture Banking 52

Astera

JANUARY 25, 2024

Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Astera

MARCH 11, 2024

It eliminates the need for complex infrastructure management, resulting in streamlined operations. According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. What are Snowflake ETL Tools? Snowflake ETL tools are not a specific category of ETL tools.

Data Warehouse 52

Data Warehouse Documentation Monitoring Data Quality 52

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.

Supply Chain 52

Supply Chain Embedded Analytics Pharmaceutical Big Data 52

Astera

APRIL 24, 2024

There are different types of data ingestion tools, each catering to the specific aspect of data handling. Standalone Data Ingestion Tools : These focus on efficiently capturing and delivering data to target systems like data lakes and data warehouses.

Data Warehouse 52

Data Warehouse Real-time Data Documentation Data Quality 52

Astera

APRIL 28, 2023

To address these challenges, approximately 44% of companies are planning to invest in artificial intelligence (AI) to streamline their data warehousing processes and improve the accuracy of their insights. AI is a powerful tool that goes beyond traditional data analytics.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Sisense

OCTOBER 7, 2019

As AI assistance learns how you want your data to look, the system can even scan all the columns and make recommendations as to what to fix, implement active learning, or go ahead and fix errors on its own, such as removing redundant records (deduplication caused by misspelling, for example) or using context clues to fill in missing values.

Artificial Intelligence 71

Artificial Intelligence Data Warehouse Monitoring Business Intelligence 71

The BAWorld

DECEMBER 23, 2023

Business Data Analyst Another distinct type is the Business Data Analyst, often seen working on data analytics projects. This role requires skills in data analytics, including knowledge of machine learning basics, artificial intelligence, and programming languages like Python.

Banking 52

Banking UML Business Analysis Business Analysis 52

Astera

SEPTEMBER 28, 2023

It’s one of many ways organizations integrate their data for business intelligence (BI) and various other needs, such as storage, data analytics, machine learning (ML) , etc. ETL provides organizations with a  single source of truth  (SSOT) necessary for accurate data analysis. What is Reverse ETL?

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

NOVEMBER 27, 2023

It’s a method used to diagnose the data’s health by thoroughly examining its structure, content, and relationships. It ensures that the data is accurate, consistent, and unique before it’s used for ETL and data analytics. It can also highlight patterns, rules, and trends within the data.

Data Mining 52

Data Mining Data Quality Business Intelligence Business Intelligence 52

Astera

MAY 14, 2024

Let’s look at some of the metadata types below: Operational metadata: details how and when data occurs and transforms. This metadata type helps to manage, monitor, and optimize system architecture performance. Examples include time stamps, execution logs, data lineage, and dependency mapping. Image by Astera.

Government 52

Government Data Governance Master Data Management Documentation 52

Astera

SEPTEMBER 4, 2023

You can use the tool to easily replicate your data in various destinations such as other databases and data warehouses. Data Transformation and Validation : Astera features a library of in-built transformations and functions, so you can easily manipulate your data as needed.

IBM Maintenance 52

IBM Maintenance IBM Support IBM cost Data Warehouse 52

Astera

AUGUST 22, 2023

Uncover hidden insights and possibilities with Generative AI capabilities and the new, cutting-edge data analytics and preparation add-ons We’re excited to announce the release of Astera 10.3—the the latest version of our enterprise-grade data management platform.

Innovation 52

Innovation Documentation Data Analytics Data Analytics 52

Astera

AUGUST 8, 2023

Data Validation: Astera guarantees data accuracy and quality through comprehensive data validation features, including data cleansing, error profiling, and data quality rules, ensuring accurate and complete data. to help clean, transform, and integrate your data.

Data Quality 52

Data Quality IBM Support IBM Maintenance Monitoring 52

Astera

SEPTEMBER 20, 2024

his setup allows users to access and manage their data remotely, using a range of tools and applications provided by the cloud service. Cloud databases come in various forms, including relational databases, NoSQL databases, and data warehouses. Common in-memory database systems include Redis and Memcached.

Data Warehouse 40

Data Warehouse Cloud Computing E-Commerce Documentation 40

Astera

AUGUST 28, 2024

For example, an influencer marketing agency will focus more on its social media activity to identify areas of improvement, and a manufacturing company will collect sensor data to assess machine performance during a period. Real-Time Analysis The processed data is analyzed instantaneously to derive immediate insights.

Big Data 52

Big Data Real-time Data Data Warehouse Monitoring 52

Actian

FEBRUARY 19, 2019

Six Sigma uses statistical monitoring techniques to identify anomalies so they can be addressed quickly before they develop into significant business impacts. The challenge with each of these approaches is the timeliness of data for making decisions. Lessons from Kaizen. Continuous improvement is happening too slowly.

Real-time Data 40

Real-time Data Supply Chain Data Warehouse Monitoring 40

Astera

OCTOBER 20, 2022

Here are some data statistics to put things into perspective: The total enterprise data volume is expected to reach 02 petabytes by the end of 2022 , which represents a 42.2 Organizations are projected to spend 212 billion US dollars on data center systems in 2022. [ii]. Industry-Specific Data Statistics.

Cloud Computing 52

Cloud Computing Healthcare Big Data Data Management 52

Actian

SEPTEMBER 12, 2019

Companies use distributed AI algorithms to monitor and optimize real-time operations – receiving inputs from embedded sensors, GPS-enabled mobile applications, IoT devices, and video cameras and aggregating this data into a holistic, digital representation of the physical operations. How AI at the edge is being used.

Data Requirement 40

Data Requirement Artificial Intelligence Data Warehouse Cloud Computing 40

Actian

SEPTEMBER 12, 2019

Companies use distributed AI algorithms to monitor and optimize real-time operations – receiving inputs from embedded sensors, GPS-enabled mobile applications, IoT devices, and video cameras and aggregating this data into a holistic, digital representation of the physical operations. How AI at the edge is being used.

Data Requirement 8

Data Requirement Artificial Intelligence Data Warehouse Cloud Computing 8

Astera

MAY 6, 2024

Best For: Businesses that require a wide range of data mining algorithms and techniques and are working directly with data inside Oracle databases. Sisense Sisense is a data analytics platform emphasizing flexibility in handling diverse data architectures. Accessible and customizable due to its open-source nature.

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

Astera

DECEMBER 21, 2022

What is unified data? Unification of data is when fragmented data sources are merged into a single repository, known as a “data warehouse.” Auditing for data protection compliance can be extremely difficult when data is processed, stored, and managed across a variety of locations and platforms.

Data Management 52

Data Management Data Governance Government Data Warehouse 52