Most organizations have their data stored in a variety of locations, right from in-house databases to external sources like cloud storage services, BI tools, and so on, and they do not want to construct and maintain a separate data pipeline; hence, they use ETL tools. Extract, transform, and load (ETL) is a data warehousing process that extracts and blends raw data from various sources, then transforms the data and eventually loads into a DW. One of the major aims of ETL is to reduce data complexity.
Let's see some of the popular ETL tools.
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The process of extracting data from source systems and bringing it into the data warehouse is commonly called ETL, which stands for extraction, transformation, and loading.
50-55 hours Training + Assignments + Actual Project Based Case Studies
All attendees will receive,
Assignment after each module, Video recording of every session
Notes and study material for examples covered.
Access to the Training Blog & Repository of Materials
In this presentation, you will find an explanation for ETL process which stands for Extraction, Transform and Load. This process is used to Extract data from different resources, transform them to a suitable form and load these data into a data warehouse. Then it will show some information about data junction tool which is used in the ETL process.
The process of extracting data from source systems and bringing it into the data warehouse is commonly called ETL, which stands for extraction, transformation, and loading.
50-55 hours Training + Assignments + Actual Project Based Case Studies
All attendees will receive,
Assignment after each module, Video recording of every session
Notes and study material for examples covered.
Access to the Training Blog & Repository of Materials
In this presentation, you will find an explanation for ETL process which stands for Extraction, Transform and Load. This process is used to Extract data from different resources, transform them to a suitable form and load these data into a data warehouse. Then it will show some information about data junction tool which is used in the ETL process.
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Ā
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This whitepaper has covered key factors related to integrations & business challenges to achieve the real digital transformation to their business. We have also explained The coding way of solving problems has its own packages and baggage's. With our study, we found that a typical customer wants to integrate a multiple systems with Salesforce system across marketing, sales, and post-sales software to make their digital transformation journey successful.
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in this slide i have tried to explain what an data engineer does and what is the difference between a data engineer and a data analytics and data scientist
Any data source becomes an SQL Query with all the power of
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Ā
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Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Product Analysis Oracle BI Applications IntroductionAcevedoApps
Ā
Oracle Business Intelligence (BI) Applications are complete, prebuilt BI solutions that deliver intuitive, role-based intelligence for everyone in an organizationāfrom front line employees to senior managementāthat enable better decisions, actions, and business processes. Designed for both āsingle sourceā and heterogeneous environments, these solutions enable organizations to gain insight from a range of data sources and applications including Siebel, Oracle E-Business Suite, PeopleSoft Enterprise, JD Edwards, and third party systems such as SAP.
Data Integration for Big Data (OOW 2016, Co-Presented With Oracle)Rittman Analytics
Ā
Set of product roadmap + capabilities slides from Oracle Data Integration Product Management, and thoughts on data integration on big data implementations by Mark Rittman (Independent Analyst)
This whitepaper has covered key factors related to integrations & business challenges to achieve the real digital transformation to their business. We have also explained The coding way of solving problems has its own packages and baggage's. With our study, we found that a typical customer wants to integrate a multiple systems with Salesforce system across marketing, sales, and post-sales software to make their digital transformation journey successful.
This tutorial covers the topics of introduction to business intelligence with examples of BI scenarios and touches upon ETL(Extract, Transform and Load) operations using SSIS on SQL 2005 & 2008 and using DTS on SQL 2000. It contains introductions to crystal reports and SSRS. It compares Data warehouse and OLAP Cube. This tutorial concludes with topics on Data Mining and Dashboards.
in this slide i have tried to explain what an data engineer does and what is the difference between a data engineer and a data analytics and data scientist
Any data source becomes an SQL Query with all the power of
Apache Spark. Querona is a virtual database that seamlessly connects any data source with Power BI, TARGIT, Qlik, Tableau, Microsoft Excel or others. It lets you build your
own universal data model and share it among reporting tools.
Querona does not create another copy of your data, unless you want to accelerate your reports and use build-in execution engine created for purpose of Big Data analytics. Just write standard SQL query and let Querona consolidate data on the fly, use one of execution engines and accelerate processing no matter what kind and how many sources you have.
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Ā
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
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https://alandix.com/academic/papers/synergy2024-epistemic/
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2. Most organizations have their data stored in a variety of
locations, right from in-house databases to external sources
like cloud storage services, BI tools, and so on, and they do
not want to construct and maintain a separate data pipeline;
hence, they use ETL tools.
3. is a data warehousing process that
extracts and blends raw data from
various sources, then transforms the data
and eventually loads into a DW. One of
the major aims of ETL is to reduce data
complexity.
Extract, Transform, and Load (ETL)
4. Letās see some of the Popular ETL Tools
Letās see some of the Popular ETL Tools
Letās see some of the Popular ETL Tools
5. ODI has great ETL capabilities that also
leverage the advantages of the database.
it does not provide the full spectrum of ETL
features.
Oracle does have features that can support
other ETL tools and solutions.
ODI works in tandem with Oracle Warehouse
Builder to handle the entire DW business
workflow dynamics.
Oracle Data Integrator (ODI)
Oracle Data Integrator (ODI)
Oracle Data Integrator (ODI)
6. It is an all-in-one, easy-to-use cloud dataāØ
platform.
It facilitates easy data integration,
management, and visualization.
Its data integration module allows
organizations to easily integrate without the
need for coding to integrate data with other
cloud applications and databases like
Amazon Redshift, Salesforce, Zendesk,
Shopify, and so on.
Skyvia
Skyvia
Skyvia
7. It is an all-in-one, fastest, most
affordable data management
platform.
Apart from ETL, it has other robust
features like data governance and
analytics.
Voracity
Voracity
Voracity
8. It is an easy-to-use, point-and-click
platform.
It has powerful transformation tools to
transform data into an analysis-friendly
form.
It has excellent customer support
features. It has a user-friendly graphical
user interface.
Xplenty
Xplenty
Xplenty
9. It is a fully customizable robust,
lightweight, and flexible data platform.
While other platforms offer low code or
no code features, CloverDX goes one
step further by allowing any aspect of
the platform to be customizable, and
this is possible using a simple built-in
scripting language.
CloverDX
CloverDX
CloverDX
10. It is a secure, scalable, and cost-
effective cloud-based DW solution that
is a part of the Amazon Web Services
cloud computing platform.
It can handle large-scale data storage,
data migration, and so on; it is all about
Big Data.
It uses massively parallel processing
(MPP) architecture which loads data at a
super-fast speed.
Amazon Redshift
Amazon Redshift
Amazon Redshift
