Why is Data Preparation Important?

Imagine building a house on a foundation of sand. No matter how impressive the blueprints or construction materials, the structure will be unstable. The same principle applies to data analysis. Inaccurate or incomplete data leads to flawed insights and potentially disastrous business decisions.
Here's how meticulous data preparation benefits organizations:

Trustworthy Insights: Clean data fosters trust in the analysis, ensuring leaders make informed decisions based on reliable information.

Improved Efficiency:Streamlined data preparation frees up valuable time for analysts to focus on higher-level tasks like uncovering trends and developing strategies.

Enhanced Accuracy: By removing errors and inconsistencies, data preparation ensures the generated insights are accurate and actionable.

Deeper Understanding: Well-prepared data empowers analysts to delve deeper, identify hidden patterns, and gain a more comprehensive understanding of business operations.

The Data Preparation Journey: A Step-by-Step Guide

While the specific steps may vary depending on the project, a typical data preparation process involves:

1. Acquiring Data: This involves identifying the necessary data, gathering it from various sources (databases, spreadsheets, etc.), and establishing secure, consistent access.
2. Exploring Data: Understanding the data's structure and quality is crucial. Analysts use data profiling techniques and visual analytics to analyze data distribution, identify missing values, and uncover potential anomalies.
3. Cleansing Data: This is where the magic happens – correcting errors, removing duplicates and outliers, and filling in missing data points to ensure data integrity.
4. Transforming Data: Data may need formatting, restructuring, or aggregation to be suitable for the intended analysis. This could involve converting date formats, pivoting tables, or calculating new variables.

Data Preparation for the Age of Big Data and Machine Learning

The rise of Big Data and machine learning has further amplified the significance of data preparation. Machine learning algorithms rely heavily on vast amounts of clean, structured data to learn and make accurate predictions.
The Challenge: Extracting value from Big Data often involves integrating data from diverse sources, each with its own structure and quality issues. Traditional data preparation methods become time-consuming and inefficient when dealing with such massive datasets.
The Solution: Modern data preparation tools like Alteryx offer a solution.

The Power of Alteryx Data Preparation

The Alteryx Analytics Automation Platform streamlines the entire data preparation process, empowering a wide range of users – data analysts, data scientists, and even citizen data scientists – to transform raw data into actionable insights. Here's how Alteryx tackles the data preparation challenge:

Speed and Efficiency: Drag-and-drop functionality and pre-built tools accelerate data preparation, freeing up valuable analyst time.

Repeatability and Automation: Alteryx workflows ensure consistent, repeatable data preparation, minimizing human error and maximizing efficiency.

Accessibility and Democratization:The user-friendly interface allows a broader range of users to participate in data preparation, fostering collaboration and knowledge sharing across teams.

Key Alteryx Features for Data Preparation:

Hundreds of pre-built tools: Alteryx boasts a vast library of tools for data cleansing, transformation, blending, and wrangling, catering to a wide range of data manipulation needs.

Intuitive drag-and-drop interface: The user-friendly interface simplifies data preparation workflows, removing technical barriers and making it accessible to users with varying skillsets.

Cloud-based scalability:Alteryx leverages the power of the cloud to handle massive datasets efficiently, ensuring scalability as data volumes grow.

Ready to Experience the Beinex -Alteryx Advantage?

Beinex’s premier partnership with Alteryx helps us enable business users to perform mundane tasks of manual data cleansing and transformation in just minutes by automating the process in a simple visual workflow that also covers advanced and predictive analytics. Thousands of organizations globally use Alteryx to deliver quick wins and high-impact business outcomes. Beinex's Alteryx consulting services amplify the transformative potential, providing tailored expertise to ensure maximum value extraction from Alteryx's powerful capabilities.

I’ve always been a huge Tableau fan as they never fail to impress me by bringing out new exciting features in every release. Tableau has yet again released a new version after a thorough research based on people’s experience, thoughts, and comments. As a result, Tableau 2020.3 has an exciting feature with respect to Predictive modelling functions, especially useful to advanced analytics geeks. There are so many other new features which everyone will appreciate – such as IN operator for calculations, Search improvements in data pane, Data quality warnings on Tableau Server and many more! Here are my top picks from the list. The IN Operator The much-awaited feature for the SQL lovers. The IN operator is a shorthand replacement for multiple OR functions. By using IN operator, we will be able to create concise calculation fields instead of never-ending lines of ‘OR’. Let’s look into a simple use case by assuming that I am interested to know the sales value of ‘Apple Products’ compared to all other products, then I can use IN operator to with IF statement to group the products to “Apple Product” and “Other Products” IF [Product Name] IN (‘Apple iPhone 5′,’Apple iPhone 5C’,’Apple iPhone 5S’) THEN “Apple Products” ELSE “Other Products” END Predictive Modelling Function Now the predictive genes would be happy to see more features on the prediction module of Tableau. With the added advantages of the functions MODEL_QUANTILE and MODEL_PERCENTILE, now the prediction function goes beyond the existing trendline analysis. Both the functions will help to build a model that understands how your data is distributed around a best-fit line. MODEL_QUANTILE is a table calculation that returns a target value at a specified percentile, based on other predictors MODEL_PERCENTILE is a table calculation that returns the probability of the expected value being less than or equal to the observed mark, based on other predictors Search improvements in Data pane While developing business specific dashboards, we need to create several calculations and its needs to be adjusted or new calculations needs to be created from existing calculations as per the business unit’s requirements. With the newly added Search improvement feature, our lives are made easy by searching or filtering specific filed based on field name, type, or comments. Search improvements in Data pane Write to external databases in Tableau Prep Write to external databases in Tableau Prep The wow moment for prep is here with the introduction of the ability to output to a database. In all previous versions of Prep, we have been able to write to an extract file or csv, and now from the latest 2020.3 introduces the ability to output to a database. Currently supported databases are SQL Server, MySQL, PostgreSQL, Amazon Redshift, Snowflake, Oracle, and Teradata. As shown in the below example, result from the flow can be saved to a data base table from the output step by choosing “Database table” option, specify your server connection (with login credentials) , choose the data base and then the table. And now, Write to database will power the analytics journey by helping to solve the issues related to, data sources, data security and data governance Open or Upload Workbooks On The Web within Tableau Server Sharing your work and exploring insights from others just got easier. You can now open a Tableau workbook or upload it straight to the web without having to use Tableau Desktop. Simply select the workbook (.twb or .twbx) you want to upload and publish directly to your site on Tableau Server or Online. Only users with the appropriate publishing permissions will have the ability to upload content. Open or Upload Workbooks On The Web within Tableau Server Three refresh options are available, they are Earlier prep was used mainly for Set Data Quality Warnings on Tableau Server Data quality warnings make it possible to let users know when a data asset is flagged, whether because the data is under maintenance, it’s stale, or some other reason. With high visibility data quality warnings, not only let users know about the issue but make sure they do not miss it. Are you interested in learning more about Tableau’s new features or the features? Are you a Tableau user and would like to become a Tableau Champion? If the answer to the above questions is a big “YES”, Please contact us at training@beinex.com/ info@beinex.com and we would be happy to schedule a Tableau demo or training for you and your company.

• List the unused data sources: Data sources imported in a workbook but not used are highlighted by the new feature. The developer can remove these data sources from the data source list to make the workbook faster.
• List of unused fields or data columns: Just like the data sources, workbook optimizer also highlights the data columns not used across the workbook. Removing these at the data source level can help improve the overall performance of the workbook.
• List of sheets not used in the dashboard: It is a common practise that developers tend to create sheets not used in the final dashboard. This creates unnecessary clutter and makes the dashboard slower. The workbook optimiser feature gives a list of such sheets which the user can delete to optimise the performance of the workbook further.
• Highlights lengthy calculations: The feature provides a list of calculations which are too complex and in turn reduce the performance of the dashboard. Simplifying a few of these can improve performance to a great extent.

The user will see a screen like below as part of the workbook optimizer. Ask Data Phrase Builder: This feature is available on Tableau Server and Tableau Online Add field would look like as shown in the below screenshot: Customize View Data: This feature is available on Tableau Server, Desktop and Tableau Online This feature enables to reshape the tabular data behind your visualisation in the View data interface. One can create new columns, remove columns from the default view, change the order and sort the data using this feature. This reshaped data can also be exported as csv file to be shared with the team. Change the root table: This feature is available on Tableau Server, Desktop and Tableau Online Managing multiple data tables becomes easier and flexible with this new feature. One can swap any table to be the root table with a single click. This allows one to change the layout of the table quickly, reshape the data with a different root table and delete a specific table without deleting child nodes. For e.g., let us assume a user had to create a data source for an analysis using 3 tables namely ‘customers’, ‘orders’ and ‘returns’. The user creates the data model such that ‘customers’ is the root table followed by ‘orders’ and ‘returns’. But after performing some analysis the user realises that ‘orders’ should be the main root table. In such cases the user would have to re-create the data again from scratch but with the new ‘Swap with root table’ feature user can do the changes with a few clicks. Parameter Enhancements in Tableau Prep In version 2022.1 Tableau Prep is adding even more places where one can use parameters in the flow as well as user enhancements. Now, one can:

• Get a list of all the parameters in one place rather than finding them in the flow. One can delete these parameters directly from the parameter window rather than to find it in the flow first.
• Include parameter names in exported output files.
• Include parameters in SQL scripts that you run before or after writing the flow output to a database. Include parameters in worksheet names when writing the flow output to Microsoft Excel.

New Visualisation Toolbar: Available on Tableau Online and Server The new feature enhances the user dashboard navigation in Tableau Online and Tableau Server. Also, the new toolbar supports embedding for your external applications. However, the available functionality within the toolbar will vary based on the user’s access level. TabPy Model Evaluation Function: This feature is available on Tableau Server, Online and Desktop A new calculation type called MODEL_EXTENSION_X has been added to Tableau specifically to call deployed models from TabPy or other analytics extensions. It gives administrators a new configuration option to control TabPy deployments by disabling the execution of arbitrary Python code. Administrators can now maintain a single source of truth in the Analytics Extension server by leveraging a central version control, while end-users have an improved experience by easily accessing deployed functions on their TabPy server and understanding the model's requirements before adding it to the tool. Apart from the above Tableau 2022.1 has other exciting features the users can look forward to including:

• 1. Improvements in Esri Data Connector
• 2. Addition of new Accelerators
• 3. Added connectors to connect to more data sources

As with the earlier version, Tableau 2022.1 which has addressed a lot of the pain points experienced by its users. Certainly, it has a lot more to offer and enhancements to look forward to. Please download the new version and explore the new features. In case of any challenges while dealing with the new features or in case you need any help related to Tableau development, please reach out to the info@beinex.com. Would be more than happy to help you on the same!

Google Cloud Platform is a Google-delivered complete set of cloud computing services. The services extend to networking, storage, application development, computing, Big Data and even more, which operate on the same cloud infrastructure used internally by Google for Gmail, YouTube, and others. What makes GCP a reliable and secure cloud infrastructure to build, test and run applications is the fact that its server has not gone down in years. IT professionals, software developers and cloud administrators can access GCP services online.

Why choose the Google Cloud Platform?

In 2022, Gartner Magic Quadrant Cloud Infrastructure and Platform services named Google as a leader for the fifth time in a row. Google Cloud Platform's global network of data centres spans multiple continents, ensuring low-latency access and redundancy for your applications and data. Therefore, GCP can be the perfect choice for organisations looking for a globally renowned cloud platform known for its wide array of services and offerings. GCP's extensive catalogue of services with unique features can be attributed to the global expansion and recognition of the platform. Some of GCP's significant services include Computing, Storage, Networking, Big Data, Cloud AI, Security and Identity Management, Management Tools, and IoT.

Besides, the following aspects also add to the reasons why GCP is a viable cloud provider for businesses:

1. Provides multi-level security to safeguard resources like assets and operating systems
2. Has a network infrastructure comprising physical, logistical, and human-resource-related elements, like wiring, routers, switches, and firewalls
3. Has proficient experts who provide support on installation and maintenance

Key Benefits of Google Cloud Platform

Optimal Pricing

GCP enables customers to access computer resources located in Google's global data centres at no cost or on a pay-per-use for the services and resources used. GCP hosting plans are cost-effective compared to other platforms and offer superior features.

Heightened Security

With features like data encryption, multi-factor authentication, and identity and access management, GCP prioritises the security of client data and applications.

Remote Accessibility

Google's web-based applications provide users with complete accessibility to GCP from virtually anywhere.

Accelerated Digital Transformation

GCP delivers enterprise-grade solution architectures and tech strategies to provide scalability and expedite digital transformation.

Dedicated Network

Google boasts its proprietary network infrastructure, granting users greater control over the functions of GCP. As a result, users experience seamless performance and heightened efficiency across the network.

Strengthened Security Infrastructure

GCP offers tools for automation, compliance and governance and a secure cloud environment to navigate challenges in cloud operations.

Leveraged AI Capabilities

GCP enables organisations to harness the power of AI to automate processes, gain data-driven insights and employ machine learning for innovation.

Big Data and Storage Options

With services like Bigtable and Cloud Storage, GCP benefits organisations in managing extensive data and facilitating real-time data processing and analysis.

Real-World Business Challenges & GCP Solutions

GCP’s suite of solutions assists organisations in tackling challenges in the dynamic business landscape effectively. Some common challenges in business and their respective GCP solutions are briefed below.

Managing large volumes of data:

GCP equips your business with analytics tools and robust data storage to manage extensive data effectively and derive valuable insights.

Driving continuous innovation:

With development and deployment tools like Cloud Functions and Google App Engine, GCP enables organisations to expedite development and gain a competitive edge.

Expanding globally:

GCP’s extensive global network infrastructure aids businesses by ensuring the applications reach across the world seamlessly.

Safeguarding against data breaches and cyberattacks:

With its suite of security tools for threat detection, data encryption and access and identity management, GCP safeguards data and applications with multi-level security.

Assuring business continuity:

In the event of unanticipated disruptions that halt business operations, GCP ensures business continuity with its backup options and disaster recovery solutions, making critical applications and data accessible.

X (formerly Twitter), eBay, PayPal, and 20th Century Fox are some of the top users who have leveraged the transformative potential of Google Cloud Platform. Being a globally recognised brand for its speed, performance, security, reliability and innovation, the Google Cloud Platform is a beacon of digital transformation for businesses navigating the challenges of the data-driven digital era. As companies venture on their journey with GCP, the prospects are endless. This partnership empowers businesses with the tools, resources, and support needed to thrive in a dynamic landscape. Whether achieving operational efficiency, reducing costs, or delivering superior customer experiences, GCP catalyses change.

What can Beinex do for you?

Beinex is now a service partner of GCP and is helping businesses advance their digital transformation endeavours by leveraging GCP’s AI capabilities, cloud infrastructure, and data analytics. Beinex offers clients expert guidance in deploying proactive solutions and using Google Cloud to make more informed data-driven decisions. This approach enables them to overcome business challenges and fosters competitiveness, efficiency, and growth. At Beinex, we deploy Google Cloud Platform as a service and the infrastructure as a service, enabling organisations to streamline access to a broader array of services and resources, resulting in cost efficiency and improved quality.