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Corporate intelligence (BI) and analytics are terms used to describe the procedures, methods, and equipment that are used by organisations to gather, examine, and decipher data in order to obtain knowledge, create wise judgements, and accomplish corporate goals. Organisations can leverage useful information produced by BI and analytics to improve strategic planning, streamline operations, and spot growth possibilities.
Data from many sources, including internal transactional systems, external data sources, and third-party data providers, is frequently used in business intelligence. Through the use of data modelling, data integration, and data cleaning processes, this data is transformed into information. After the data has been prepared, it can be analysed and visualised using a variety of analytical approaches, including advanced analytics, reporting, dashboards, and data visualisation.
The process of analysing data to find patterns, trends, and insights that might guide decision-making is known as analytics. Analytics can be diagnostic, predictive, prescriptive, or descriptive. Diagnostic analytics involves analysing historical data to understand what happened in the past. Predictive analytics uses data to make forecasts or predictions about the future. Prescriptive analytics involves recommending actions to maximise outcomes.
Finance, marketing, sales, supply chain management, human resources, and operations are just a few of the company functions that use business intelligence and analytics. Businesses utilise BI and analytics to learn more about their operations, clients, markets, and rivals. These insights help them plan strategically, streamline their operations, and boost performance.
With the introduction of new technologies like big data, artificial intelligence (AI), machine learning, and sophisticated data visualisation tools in recent years, the discipline of business intelligence and analytics has advanced. Organisations are now able to handle and analyse massive amounts of data in real-time, leading to the discovery of fresh insights and potential for innovation.
Technoforte specializes in providing Business Intelligence services, Power BI Dashboard Design, Power BI reports, Qlik Business services and Business Intelligence solutions for various business verticals, which include Manufacturing, Banking, Insurance, Telecom, Finance and varied Services.
Technoforte provides data cleansing services. Easy availability of clean data from multiple sources into one comprehensive database is essential for any business analytics need. Extract, transform, load (ETL) and extract, load, transform (E-LT) are the two main approaches used to build a data warehouse.
Turn the data from multiple sources into actionable insights for decision-making. Technoforte understands your reporting requirements and how the team uses the dashboards at various levels of the organization. The summary graphs can be drilled down to the required information by the users. The right visualization (graphs, bars, charts, lines, gauge, funnel, maps etc.) is used based on the user requirement. Self-service BI is suggested and implemented to give more power to the tech savvy business users. A question and answer visual can also be designed using Natural Language.
Making predictions based on historical data and analytics techniques such as statistical modelling and machine learning. A binary prediction model can be created using dataflow and training the entities in the dataflow for machine learning. This can help create scored data reports for better prediction. Technoforte BI team can help customers setup dataflows, link tables from other dataflows and set up s predictive model using tools such as Power BI, Qlik Sense or Tableau.
Analyse high (growing) volumes of structured transaction data and unstructured data that are often left untapped by conventional BI and analytics program. With ease of data collection and storage, the challenge is how effective this data is used by the organization. The key is to be able to store and organize data and also use it for data insights at the same time. Cutting edge datawarehouse tools like Snowflake and BigQuery are used for this purpose. The Technoforte team can help companies collect data from disparate data sources, store and cleanse data, understand company’s requirement and form data sets, identify trends, patterns and data relations, setup a Machine Learning Model and implement the relevant visualization tools.
The Technoforte specializes in Data Migration from one BI tool to another, e.g. Qlik to Power BI or vice versa. Data Integration and Migration, is a subject very dear to Technoforte, as the power of BI can only be unravelled when proper integration processes, procedures and tools are used.
Technoforte team can consult organizations with data governance policies and selection/implementation of right tools, which can help users across the organization in effective use of accumulated business data. This will be keeping in mind data security, quality data availability and compliance with regulatory bodies. For example, setting up a data warehouse helps right from data collection, data storage, data availability, data retirement, data security and policy compliance. Good data governance not only drives data democratization, but also increases employees and customers trust, helps data driven decision making and increases an organizations brand value.
Data Warehousing
Technoforte provides data cleansing services. Easy availability of clean data from multiple sources into one comprehensive database is essential for any business analytics need. Extract, transform, load (ETL) and extract, load, transform (E-LT) are the two main approaches used to build a data warehouse.
Data Analytics & Design
Turn the data from multiple sources into actionable insights for decision-making. Technoforte understands your reporting requirements and how the team uses the dashboards at various levels of the organization. The summary graphs can be drilled down to the required information by the users. The right visualization (graphs, bars, charts, lines, gauge, funnel, maps etc.) is used based on the user requirement. Self-service BI is suggested and implemented to give more power to the tech savvy business users. A question and answer visual can also be designed using Natural Language.
Predictive Analytics.
Making predictions based on historical data and analytics techniques such as statistical modelling and machine learning. A binary prediction model can be created using dataflow and training the entities in the dataflow for machine learning. This can help create scored data reports for better prediction. Technoforte BI team can help customers setup dataflows, link tables from other dataflows and set up s predictive model using tools such as Power BI, Qlik Sense or Tableau.
Big Data
Analyse high (growing) volumes of structured transaction data and unstructured data that are often left untapped by conventional BI and analytics program. With ease of data collection and storage, the challenge is how effective this data is used by the organization. The key is to be able to store and organize data and also use it for data insights at the same time. Cutting edge datawarehouse tools like Snowflake and BigQuery are used for this purpose. The Technoforte team can help companies collect data from disparate data sources, store and cleanse data, understand company’s requirement and form data sets, identify trends, patterns and data relations, setup a Machine Learning Model and implement the relevant visualization tools.
Data Integration and Data Migration
The Technoforte specializes in Data Migration from one BI tool to another, e.g. Qlik to Power BI or vice versa. Data Integration and Migration, is a subject very dear to Technoforte, as the power of BI can only be unravelled when proper integration processes, procedures and tools are used.
Data Governance
Technoforte team can consult organizations with data governance policies and selection/implementation of right tools, which can help users across the organization in effective use of accumulated business data. This will be keeping in mind data security, quality data availability and compliance with regulatory bodies. For example, setting up a data warehouse helps right from data collection, data storage, data availability, data retirement, data security and policy compliance. Good data governance not only drives data democratization, but also increases employees and customers trust, helps data driven decision making and increases an organizations brand value.
Creating a truly agile, data-driven organization takes more than just a visualization tool alone. Qlik’s open data analytics platform supports a complete portfolio of solutions that provide advanced analytics across the spectrum of BI needs. That means more people can discover more insights to create greater business value.
It’s important to note that these are potential developments Qlik, as a leading BI and Analytics company may undertake. Future development will also be determined by what the customer actually wants.
Power BI is a business analytics solution that lets you visualize your data and share insights across your organization, or embed them in your app or website. Connect to hundreds of data sources and bring your data to life with live dashboards and reports.
Enterprise Analytics with Self Service.
Power BI is enterprise analytics platform with Self Service capabilities on a single platform. This empowers users to create their own KPI reducing dependencies on the IT.
Big data management with Azure
Organisation can analyse huge volume of data by using Azure Data lake. Power BI can help in get instant insights, collaboration with all the stake holders.
Industry-leading AI ready platform
Power BI platform provide latest advances in Microsoft AI to prepare data, build machine learning models. Organisation can develop KPI for quick insights from both structured and unstructured data, including text and images.
Action on Story and Insights
Main goal of BI to help user firm up actions based on the stories and insights. Combining POWER BI, Power APPs to easily build business application and automate work flows.
Real time Analytics
Access to real-time analytics which shall enable to make timely decisions.
1.Enterprise Analytics with Self Service.
Power BI is enterprise analytics platform with Self Service capabilities on a single platform. This empowers users to create their own KPI reducing dependencies on the IT.
2.Big data management with Azure
Organisation can analyse huge volume of data by using Azure Data lake. Power BI can help in get instant insights, collaboration with all the stake holders.
3.Industry-leading AI ready platform
Power BI platform provide latest advances in Microsoft AI to prepare data, build machine learning models. Organisation can develop KPI for quick insights from both structured and unstructured data, including text and images.
4.Action on Story and Insights
Main goal of BI to help user firm up actions based on the stories and insights. Combining POWER BI, Power APPs to easily build business application and automate work flows.
5.Real time Analytics
Access to real-time analytics which shall enable to make timely decisions.
It’s important to note that these predictions are speculative in nature and based on todays’ trends and technologies. The actual future developments of Power BI may be different, depending on multiple factors, market requirements, technological factors and Microsoft’s product roadmap.
Data integration and migration are critical aspects of business intelligence and analytics, as they involve the process of extracting, transforming, and loading (ETL) data from various sources into a data warehouse or analytics platform for analysis and reporting. Here are some key considerations for data integration and migration specific to business intelligence and analytics:
Finally, while we conclude this topic, it should be noted that data migration and integration are essential parts of business intelligence and analytics, and care should be taken to ensure that these procedures are effective, scalable, performant, secure, and in compliance with data privacy laws. To guarantee correct and trustworthy data for analysis and reporting, it is crucial to do proper data transformation, data mapping, data quality assurance, metadata management, and monitoring.
Business users may access, analyse, and visualise data with the use of a variety of tools, technologies, and practises known as self-service business intelligence (BI). It gives non-technical individuals the ability to analyse data independently and come up with insights without depending on IT teams or professional data analysts to create and distribute reports or dashboards.
Self-service BI typically involves the use of user-friendly and intuitive data visualization and analytics tools that allow business users to explore data, create reports, and generate insights through a self-service interface. These tools often provide drag-and-drop interfaces, pre-built templates, and interactive visualizations that enable users to easily manipulate data, create charts, and design reports without requiring coding or technical skills.
In general, self-service BI empowers business users to become more data-driven, independent, and quick in their decision-making processes, improving business results and giving them a competitive edge.
Yes, a major development in BI and analytics is the growing usage of cloud-based Business Intelligence (BI) tools. When BI tools and technologies are used on cloud platforms like Amazon Web Services (AWS), Microsoft Azure, Google Cloud, and others, where data and analytics resources are stored and processed in the cloud, this is referred to as cloud-based BI.
To guarantee that their data is secure and complies with legal requirements, organisations must carefully evaluate data security, privacy, and compliance needs before using cloud-based BI solutions.
Overall, the adoption of cloud-based BI is growing because it provides businesses with advantages including scalability, flexibility, cost savings, simplicity of deployment and maintenance, accessibility, collaboration and sophisticated analytical capabilities, making it an important trend in the BI and analytics industry.
A key development in the realm of business intelligence (BI) and analytics is the introduction of augmented analytics. Using cutting-edge technology, such as machine learning and artificial intelligence (AI), to automate and improve several steps of the analytics process, such as data preparation, data analysis, and insight creation, is known as augmented analytics.
By automating and enhancing conventional analytics processes with cutting-edge technology, augmented analytics is revolutionising how organisations approach data analysis and decision-making. The future of BI and analytics is anticipated to be shaped by this trend, which will allow businesses to get deeper insights from their data, make better decisions, and provide better business results.
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