Data Warehouse Online Training Course in ACTE. A data warehouse is a type of data management system that is designed to enable and support business intelligence (BI) activities, especially analytics. Data warehouses are solely intended to perform queries and analysis and often contain large amounts of historical data.
A data warehouse is a system that pulls together data from many different sources within an organization for reporting and analysis. The reports created from complex queries within a data warehouse are used to make business decisions.
Good news for data warehouse analysts, and those aspiring to start a career in the field: They're in demand. Their role is critical to a company's ability to make sound business decisions. A data warehouse analyst collects, analyzes, mines and helps the business leverage the information stored in data warehouses.
Future will be always safe for DW knowledgeable persons. Data warehousing is wider term used for ETL and necessary data storage and OLAP tool developments for relational databases and is not going to finish in new future.Now because of Big Data era, just terms got changed as Data Lakes for storage mechanism but original concepts will be the same.
7 Steps to Data Warehousing
- Determine Business Objectives.
- Collect and Analyze Information.
- Identify Core Business Processes.
- Construct a Conceptual Data Model.
- Locate Data Sources and Plan Data Transformations.
- Set Tracking Duration.
- Implement the Plan.
The key characteristics of a data warehouse are as follows:
- Some data is denormalized for simplification and to improve performance.
- Large amounts of historical data are used.
- Queries often retrieve large amounts of data.
- Both planned and ad hoc queries are common.
- The data load is controlled.
Data warehouse allows users to access critical data from the number of sources in a single place. Therefore, it saves user's time of retrieving data from multiple sources. Data warehouse stores a large amount of historical data. This helps users to analyze different time periods and trends to make future predictions.
It depends on how many people you put on the project, how experienced the team is, etc. 1 year would be considered long; for new projects, you probably will provide 2 or 3 dashboards of 10 - 15 KPIs each, with a Data Warehouse. 8 months will provide the Data Warehouse and 1 comprehensive Dashboard.
Data warehousing was born out of the need to consolidate data across multiple enterprise systems, in order to serve metrics across an organization. The requirements to do this type of work include things like ETL, SQL, data modeling star and snowflake schemas.
Best way to learn data warehousing is to study all the theoretical concepts first, then looking at an use case, and then understanding the various criteria to be considered/followed for designing databases. You can start with tutorialspoint.
The answer is pretty easy, actually: There is currently no viable on-premise competition for what cloud data warehouses provide. Organizations are moving to cloud data warehousing technologies for the reasons of Performance, Security, Agility, and operational simplification.
- Teradata. Teradata is a market leader in the data warehousing space that brings more than 30 years of history to the table.
- Oracle. Oracle is basically the household name in relational databases and data warehousing and has been so for decades.
- Amazon Web Services (AWS)
- Cloudera.
- MarkLogic.
- A data warehouse will make it easier to get to the answers you need, when you need them.
- The data warehouse is organized around groups of tables that each focus on ONE business process.
- Change.
Why Data Warehousing is the Best Career Move
If you are still not convinced by the fact that Data Warehousing is one of the hottest skills, here are 10 more reasons for you
Soaring Demand for Analytics Professionals:
- Data is useless without the skill to analyze it.There are more job opportunities in Big Data management and Analytics than there were last year and many IT professionals are prepared to invest time and money for the training.
Huge Job Opportunities & Meeting the Skill Gap:
- The demand for Analytics skill is going up steadily but there is a huge deficit on the supply side. This is happening globally and is not restricted to any part of geography. In spite of Data Warehousing being a ‘Hot’ job, there is still a large number of unfilled jobs across the globe due to shortage of required skill.
- A McKinsey Global Institute study states that the US will face a shortage of about 190,000 data scientists and 1.5 million managers and analysts who can understand and make decisions using Big Data by 2020.
To get in-depth knowledge on Data Science, you can enroll for live Data Science Certification Training by ACTE with 24/7 support and lifetime access.
Salary Aspects:
- Strong demand for Data Analytics skills is boosting the wages for qualified professionals and making Big Data pay big bucks for the right skill. This phenomenon is being seen globally where countries like Australia and the U.K are witnessing this ‘Moolah Marathon’.
- According to the 2020 Skills and Salary Survey Report published by the Institute of Analytics Professionals of Australia (IAPA), the annual median salary for data analysts is $130,000, up four per cent from last year. Continuing the trend set in 2020 the median respondent earns 184% of the Australian full-time median salary.
- The rising demand for analytics professionals is also reflected in IAPA’s membership, which has grown to more than 5000 members in Australia.
Data Warehousing : A Top Priority in a lot of Organizations
- According to the ‘Peer Research – Data Warehousing ’ survey, it was concluded that Data Warehousing is one of the top priorities of the organizations participating in the survey as they believe that it improves the performances of their organizations.
- Based on the responses, it was found that approximately 45% of the surveyed believe that Data Warehousing will enable much more precise business insights, 38% are looking to use Analytics to recognize sales and market opportunities. More than 60% of the respondents are depending on Data Warehousing to boost the organization’s social media marketing abilities.
Adoption of Data Warehousing is Growing:
- New technologies are now making it easier to perform increasingly sophisticated data analytics on a very large and diverse datasets. This is evident as the report from The Data Warehousing Institute (TDWI) shows. According to this report, more than a third of the respondents are currently using some form of advanced analytics on Big Data, for Business Intelligence, Predictive Analytics and Data Mining tasks.
- With Data Warehousing providing an edge over the competition, the rate of implementation of the necessary Analytics tools has increased exponentially. In fact, most of the respondents of the ‘Peer Research – Data Warehousing ’ survey reported that they already have a strategy setup for dealing with Data Warehousing . And those who are yet to come up with a strategy are also in the process of planning for it.
Analytics: A Key Factor in Decision Making
- Analytics is a key competitive resource for many companies. There is no doubt about that. According to the ‘Analytics Advantage’ survey overseen by Tom Davenport, ninety six percent of respondents feel that analytics will become more important to their organizations in the next three years. This is because there is a huge amount of data that is not being used and at this point, only rudimentary analytics is being done. About forty nine percent of the respondents strongly believe that analytics is a key factor in better decision-making capabilities. Another sixteen percent like it for its superior key strategic initiatives.
- Even though there is a fight for the title of ‘Greatest Benefit of Data Warehousing ’, one thing is undeniable and stands out the most: Analytics play an important role in driving business strategy and making effective business decisions.
The Rise of Unstructured and Semistructured Data Analytics:
- The ‘Peer Research – Data Warehousing ’ survey clearly reports that there is a huge growth when it comes to unstructured and semistructured data analytics. Eighty four percent of the respondents have mentioned that the organization they work for are currently processing and analyzing unstructured data sources, including weblogs, social media, e-mail, photos, and video. The remaining respondents have indicated that steps are being taken to implement them in the next 12 to 18 months.
Data Warehousing is Used Everywhere!
- It is a given that there is a huge demand for Data Warehousing owing to its awesome features. The tremendous growth is also due to the varied domain across which Analytics is being utilized. The image below depicts the job opportunities across various domains.
Surpassing Market Forecast / Predictions for Data Warehousing :
Data Warehousing has topped a survey carried out by Nimbus Ninety, as the most disruptive technologies that will have the biggest influence in three years’ time. Added to this, there are more market forecasts that support this:
- According to IDC, the Data Warehousing market will reach $125 billion worldwide in 2020.
- IIA states that Data Warehousing tools will be the first line of defense, combining machine learning, text mining and ontology modeling to provide holistic and integrated security threat prediction, detection, and deterrence and prevention programs.
- According to the survey ‘The Future of Data Warehousing – Global Market and Technologies Forecast – 2020, Data Warehousing Global Market will grow by 14.4% CAGR over this period.
- The Data Warehousing Global Market for Apps and Analytics Technology will grow by 28.2% CAGR, for Cloud Technology will grow by 16.1% CAGR, for Computing Technology will grow by 7.1% CAGR, for NoSQL Technology will grow by 18.9% CAGR over the entire 2015-2020 period.
Numerous Choices in Job Titles and Type of Analytics :
From a career point of view, there are so many option available, in terms of domain as well as nature of job. Since Analytics is utilized in varied fields, there are numerous job titles for one to choose from.
- Data Warehousing Business Consultant
- Data Warehousing Architect
- Big Data Engineer
- Big Data Solution Architect
- Big Data Analyst
- Analytics Associate
- Business Intelligence and Analytics Consultant
- Metrics and Analytics Specialist
Data Warehousing career is deep and one can choose from the 3 types of data analytics depending on the Big Data environment.
- Prescriptive Analytics
- Predictive Analytics
- Descriptive Analytics.